CN114969518A - Scientific and technological service resource recommendation system based on enterprise user requirements - Google Patents
Scientific and technological service resource recommendation system based on enterprise user requirements Download PDFInfo
- Publication number
- CN114969518A CN114969518A CN202210517702.1A CN202210517702A CN114969518A CN 114969518 A CN114969518 A CN 114969518A CN 202210517702 A CN202210517702 A CN 202210517702A CN 114969518 A CN114969518 A CN 114969518A
- Authority
- CN
- China
- Prior art keywords
- service
- scientific
- quality
- enterprise user
- technological
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 claims abstract description 8
- 238000005516 engineering process Methods 0.000 claims description 34
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000011156 evaluation Methods 0.000 claims description 16
- 238000001514 detection method Methods 0.000 claims description 9
- 238000011534 incubation Methods 0.000 claims description 9
- 238000012216 screening Methods 0.000 claims description 9
- 150000001875 compounds Chemical class 0.000 claims description 8
- 238000013139 quantization Methods 0.000 claims description 8
- 238000011161 development Methods 0.000 claims description 7
- 238000007689 inspection Methods 0.000 claims description 5
- 238000012827 research and development Methods 0.000 claims description 5
- 238000012546 transfer Methods 0.000 claims description 5
- 238000010606 normalization Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000011002 quantification Methods 0.000 claims description 2
- 239000000126 substance Substances 0.000 claims description 2
- 238000013475 authorization Methods 0.000 description 5
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/18—Legal services
- G06Q50/184—Intellectual property management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Marketing (AREA)
- Technology Law (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a scientific and technological service resource recommendation system based on enterprise user requirements, which comprises a data acquisition module, a set generation module, an enterprise user requirement acquisition module, a scientific and technological service resource providing acquisition module, an enterprise user requirement and scientific and technological service resource matching module and a scientific and technological service resource recommendation module, wherein the data acquisition module is used for acquiring a set of scientific and technological service resources; the enterprise user requirement and scientific and technological service resource matching module comprises a requirement service type matching module, a requirement service quality matching module and a comprehensive matching module. The method and the system can effectively and accurately reflect the degree of the requirement of the enterprise user on the service quality, accurately match the requirement of the enterprise user with the provided scientific and technological service resources, and recommend the optimal scientific and technological service resources to the enterprise user according to the requirement of the enterprise user.
Description
Technical Field
The invention relates to the technical field of intelligent recommendation, in particular to a scientific and technological service resource recommendation system based on enterprise user requirements.
Background
With the development of the traditional science and technology service industry and the rapid development of the emerging science and technology service industry, the science and technology service platform will become an important channel for providing science and technology services in the science and technology service industry. The scientific and technological services in the scientific and technological service platform are professional services provided for various innovation subjects such as enterprises, and enterprise users are a great master in platform user types. At present, as the innovation abilities and the development stages of different enterprise users in a scientific and technological service platform are different, the requirements for scientific and technological services are complicated and diversified; in addition, as the number of scientific and technological service resources with similar functions in the scientific and technological service platform becomes more and more, it becomes more and more difficult for enterprise users to quickly match the scientific and technological service resources meeting the needs of the users.
At present, a metering analysis method is mainly adopted for obtaining user requirements, and the user requirements are obtained in a mode of designing, issuing and analyzing questionnaires. However, the acquisition method estimates the needs of most users according to the needs of small sample users, and has certain difficulty in selecting sample users, and the difference of sample user distribution may cause great difference of user needs, and the subjectivity is strong.
The mainstream recommendation algorithm adopted by the current recommendation system mainly comprises a recommendation algorithm based on association rules, a recommendation algorithm based on content, a recommendation algorithm based on collaborative filtering and the like. For example, association rule based recommendation algorithms analyze user records using association rule techniques, mine user needs based on the inherent relationships of individual products or services during the sales process, and generate recommendations based on the need information. The recommendation algorithms only consider common attributes of all scientific and technological service resources, such as availability, reliability and cost performance, but not special attributes contained in different scientific and technological service resource categories (such as scientific and technological popularization, scientific and technological consultation, inspection and detection, scientific and technological finance, research and development, entrepreneurship incubation, technical transfer and special attributes of intellectual property rights in different scientific and technological service resource categories are respectively science popularization expenditure, consultation effective rate, detection result effective rate, total financing amount, development service amount, incubation enterprise amount, technical talent amount and patent value degree).
At present, there are few patents on technology service resource recommendation. The scientific and technological service recommendation and the cloud manufacturing service recommendation have similarities, and both provide safe and reliable service resources which are used as required for users through a shared service platform. They also have the characteristics of platform openness, service provider universality and complexity of user requirements, and the problem of how to select satisfactory service resources from a large number of service resources by users.
Therefore, realizing scientific and technological service resource recommendation required by enterprise users is a problem to be solved urgently by the current scientific and technological service platform.
Disclosure of Invention
The invention provides a scientific and technological service resource recommendation system based on enterprise user requirements, which can recommend optimal scientific and technological service resources to enterprise users according to the requirements of the enterprise users.
In order to achieve the purpose, the scientific and technological service resource recommendation system based on enterprise user requirements is researched, and is characterized by comprising a data acquisition module, a set generation module, an enterprise user requirement acquisition module, a scientific and technological service resource providing acquisition module, an enterprise user requirement and scientific and technological service resource matching module and a scientific and technological service resource recommendation module; wherein the content of the first and second substances,
the data acquisition module is used for acquiring an enterprise user list, scientific and technological service requirement details and service quality requirements issued by an enterprise user demander on a scientific and technological service platform and acquiring scientific and technological service resource data issued by a service resource provider on the scientific and technological service platform;
the collection generation module is used for collecting an enterprise user list with requirements on scientific and technological service resources on the scientific and technological service platform to form an enterprise user demand party collection P; collecting scientific and technological service resources of corresponding categories for each enterprise user on the scientific and technological service platform according to the respective required scientific and technological service resource categories of each enterprise user in the enterprise user demand side set P to form a scientific and technological service resource set S which corresponds to the enterprise users one by one;
the enterprise user demand acquisition module is used for acquiring a demand type Ptype, a plurality of literal demand service quality common attributes PQ and a literal demand service quality special attribute PQ which are provided by each enterprise user in the enterprise user demand party set P aiming at the scientific and technological service resource category of respective demand, and combining the plurality of literal demand service quality common attributes PQ and the literal demand service quality special attribute PQ to construct a demand service quality attribute index PQoS; performing corresponding literal grade evaluation on a plurality of literal required service quality common attributes PQ in a required service quality attribute index PQoS, then performing fuzzy quantization on the corresponding literal grade evaluation, and performing corresponding range quantization on the literal required service quality special attribute PQ in the required service quality attribute index PQoS, thereby obtaining a digital required service quality common attribute PQ and a digital required service quality special attribute PQ;
the technical service resource providing and acquiring module is used for acquiring a providing type Stype corresponding to a requirement type Ptype issued by each technical service resource in a technical service resource set S corresponding to an enterprise user one by one, a plurality of digital providing service quality common attributes SQ corresponding to a plurality of literal requiring service quality common attributes PQ and digital providing service quality special attributes SQ corresponding to the literal requiring service quality special attributes PQ, and combining the plurality of digital providing service quality common attributes SQ and the digital providing service quality special attributes SQ to construct a providing service quality attribute index SQoS;
the enterprise user demand and science and technology service resource matching module comprises a demand service type matching module, a demand service quality matching module and a comprehensive matching module;
the demand service type matching module is used for carrying out type matching similarity Simt calculation on the demand type Ptype and the provided type Stype of each scientific and technological service resource in the scientific and technological service resource set S corresponding to the enterprise user one by one, screening out scientific and technological service resource data which are not matched with the demand type Ptype, reserving the residual scientific and technological service resource data which are matched with the demand type Ptype, and forming a candidate service resource set corresponding to the enterprise user one by one;
the demand service quality matching module is used for carrying out normalization processing on a digital demand service quality common attribute PQ and an original attribute value corresponding to a digital demand service quality special attribute PQ in a demand service quality attribute index PQoS to obtain a demand service quality attribute value vector P' QoS; meanwhile, in a candidate service resource set corresponding to enterprise users one by one, normalizing a common attribute SQ of digital service quality provided in a service quality providing attribute index SQoS of each scientific and technical service resource and an original attribute value corresponding to a special attribute SQ of digital service quality provided to obtain a service quality providing attribute value vector S' QoS; performing service quality similarity Simq calculation on the required service quality attribute value vector P 'QoS and the provided service quality attribute value vector S' QoS to determine a service quality matching similarity threshold; screening out scientific and technological service resource data with the service quality similarity Simq smaller than the service quality matching similarity threshold, and reserving the rest scientific and technological service resource data with the service quality similarity Simq larger than or equal to the service quality matching similarity threshold to form a selected service resource set corresponding to the enterprise users one by one;
the comprehensive matching module is used for carrying out comprehensive weighted similarity calculation on the type matching similarity Simt and the service quality similarity Simq of each scientific and technological service resource in the selected service resource set corresponding to the enterprise user one by one to obtain the comprehensive matching similarity Sim (P, S) of each scientific and technological service resource in the corresponding selected service resource set;
the scientific and technological service resource recommending module is used for comparing the comprehensive matching similarity Sim (P, S) of all scientific and technological service resources in the carefully selected service resource set corresponding to the enterprise users one by one with a comprehensive matching similarity threshold, deleting the scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is smaller than the comprehensive matching similarity threshold, reserving the remaining scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is larger than or equal to the comprehensive matching similarity threshold, performing descending order arrangement according to the numerical value of the comprehensive matching similarity Sim (P, S), and pushing the scientific and technological service resource with the maximum numerical value of the comprehensive matching similarity Sim (P, S) to the corresponding enterprise user in the enterprise user demand side set P.
The invention has the advantages that:
1. firstly, carrying out type matching similarity calculation on the demand type of an enterprise user in an enterprise user demand party set P and the provision type of scientific and technological service resources in a scientific and technological service resource set S, and screening out scientific and technological service resource data which are not matched with the demand type in the scientific and technological service resource set to obtain a candidate service resource set; then, the service quality similarity of the required service quality of the enterprise user and the provided service quality of the scientific and technological service resources in the candidate service resource set is calculated, the scientific and technological service resource data with low service quality similarity are screened out, and a selected service resource set is obtained; and then, carrying out comprehensive weighted similarity calculation on the scientific and technological service resource data in the selected service resource set, screening out the scientific and technological service resource data with lower comprehensive weighted similarity, and carrying out descending order arrangement on the residual scientific and technological service resources in the selected service resource set according to the comprehensive matching similarity numerical value, thereby obtaining the scientific and technological service resource with the maximum comprehensive matching similarity Sim (P, S) numerical value, namely the optimal service resource required by the enterprise user.
2. The method divides the required service quality of enterprise users into two parts of common attribute of the characters and special attribute of the characters, quantifies the common attribute requirement of the characters by using a fuzzy model, converts the attribute requirement of the characters into the attribute requirement of the figures, and considers the special attribute requirement, thereby avoiding the subjectivity defect of quality requirement acquisition, enhancing the objectivity of quality requirement acquisition and effectively and accurately reflecting the required degree of the enterprise users on the service quality;
3. the method carries out comprehensive weighted similarity calculation on the introduced type matching similarity calculation and the introduced service quality similarity calculation, and improves the accuracy of the recommendation result;
the scientific and technological service resource recommendation system based on the enterprise user requirements can effectively and accurately reflect the degree of the requirement of the enterprise user on the service quality, accurately match the requirement of the enterprise user with the provided scientific and technological service resources, and recommend the optimal scientific and technological service resources to the enterprise user according to the requirement of the enterprise user.
Drawings
FIG. 1 is a flowchart illustrating an embodiment of a scientific and technological service resource recommendation system based on enterprise user requirements;
in the figure: the system comprises a data acquisition module 1, a set generation module 2, an enterprise user demand acquisition module 3, a scientific and technological service resource providing acquisition module 4, an enterprise user demand and scientific and technological service resource matching module 5 and a scientific and technological service resource recommendation module 6;
the enterprise user requirement and scientific and technological service resource matching module 5 comprises: a demand service type matching module 5-1, a demand service quality matching module 5-2 and a comprehensive matching module 5-3.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific embodiments.
The scientific and technological service resource recommendation system based on enterprise user requirements, as shown in fig. 1, comprises a data acquisition module 1, a set generation module 2, an enterprise user requirement acquisition module 3, a scientific and technological service resource providing acquisition module 4, an enterprise user requirement and scientific and technological service resource matching module 5 and a scientific and technological service resource recommendation module 6.
The data acquisition module 1 is used for acquiring an enterprise user list, scientific and technological service requirement details and service quality requirements issued by an enterprise user demander on a scientific and technological service platform, and acquiring scientific and technological service resource data issued by a service resource provider on the scientific and technological service platform.
Specifically, a pig sika ring website is provided on the certain technology service platform. Intellectual property service and enterprise user data in the pig eight-ring website are collected as a data set. The intellectual property service contains 12764 pieces of data of patents, domain names, trademarks and websites. There are 3645 pieces of enterprise user data.
The set generation module 2 is used for collecting an enterprise user list with requirements on scientific and technological service resources on the scientific and technological service platform to form an enterprise user demand party set P; and collecting scientific and technological service resources of corresponding categories for each enterprise user on the scientific and technological service platform according to the respective required scientific and technological service resource categories of each enterprise user in the enterprise user demand side set P to form a scientific and technological service resource set S which corresponds to the enterprise users one by one.
Specifically, the scientific and technological service resource categories include scientific and technological popularization, scientific and technological consultation, inspection and detection, scientific and technological finance, research and development, entrepreneurship incubation, technical transfer and intellectual property rights.
Take intellectual property service in science and technology service category as an example, set 3 enterprise users, P i The expression ((i ═ 1,2,3) needs the science and technology service, the science and technology service platform comprises 12764 available intellectual property service resources, and S is used i And (i) 1,2, …, 12764. The enterprise user requirement acquisition module 3 is used for acquiring a requirement type Ptype, a plurality of literal requirement service quality common attributes PQ and a literal requirement service quality special attribute PQ which are provided by each enterprise user in the enterprise user requirement party set P aiming at the scientific and technological service resource category of respective requirements, and combining the plurality of literal requirement service quality common attributes PQ and the literal requirement service quality special attribute PQ to construct a requirement service quality attribute index PQoS; corresponding literal grade evaluation is carried out on a plurality of literal required service quality common attributes PQ in a required service quality attribute index PQoS, then fuzzy quantization is carried out on the corresponding literal grade evaluation, and corresponding range quantization is carried out on the literal required service quality special attribute PQ in the required service quality attribute index PQoS, so that the digital required service quality common attribute PQ and the digital required service quality special attribute PQ are obtained.
Specifically, the type Ptype of the demand provided by three enterprise users in Pi for the scientific and technological service resource is "invention authorization", and the common attribute PQ of the multiple literal demand service qualities and the corresponding literal rank evaluation and fuzzy quantization are shown in table 1.
TABLE 1 required QoS common Attribute degrees of Enterprise Users for scientific and technological service resources
As shown in table 1, the required quality of service common attribute PQ is a common requirement, such as manageability, stability, and purchasing power, provided by each enterprise user for the type of scientific and technological service resource required by each enterprise user. The fuzzy quantification method for the ranking evaluation of the characters adopts a triangular fuzzy evaluation method, and the triangular fuzzy evaluation method specifically comprises the following steps: the evaluation of the degree of the literary property is divided into seven degree grades of 'very low', 'low medium', 'medium low', 'medium', 'high', 'very high', each degree grade is quantified through a respective matched membership equation, and a quantified value is represented by a triangular fuzzy number M (l, M, u), wherein l is less than or equal to M and less than or equal to u, l and u respectively represent a lower boundary and an upper boundary of M, M is a median of M, and M (l, M, u) represents a deviation degree of M relative to M.
The demand service quality common attribute PQ is a common requirement, such as manageability, stability and purchasing power, provided by each enterprise user for the type of scientific and technological service resources required by each enterprise user; the special attribute PQ of the required service quality is a special requirement provided by each enterprise user for the type of the scientific and technological service resources required by each enterprise user, such as popular science expenses, effective consultation rate, effective detection result rate, total financing amount, development service amount, incubation enterprise amount, technical talent amount and patent value degree.
The required quality of service attribute index PQoS is expressed as,
PQoS＝{PQ 1 ,PQ 2 ,PQ 3 ,……∣PQ n }
in the formula (I), the compound is shown in the specification,
PQ 1 the 1 st demanded quality of service common attribute, e.g., manageability as in table 1,
PQ 2 the 2 nd required quality of service common attribute, such as stability in table 1,
PQ 3 the 3 rd required quality of service common attribute, such as purchasing power in table 1,
PQ n and providing special attribute of required service quality for each enterprise user in the enterprise user demand side set P. The special attributes of scientific and technological popularization, scientific and technological consultation, inspection and detection, scientific and technological finance, research and development, entrepreneurship incubation, technical transfer and intellectual property rights are respectively science popularization expenditure, effective consultation rate, effective detection result rate, total financing amount, development service amount, incubation enterprise number, technical talent amount and patent value degree.
As shown in Table 2, the literal QoS (quality of service) common attribute PQ proposed by each enterprise user in the set P of enterprise user demander is given 1～3 Literal demand quality of service special attribute PQ 11 And a required quality of service common attribute PQ for text 1～3 Digitalizing, and requiring the special attribute PQ of the quality of service for the characters 11 Range quantization is performed.
TABLE 2 Enterprise user P i Demand for scientific and technological service resources
The scientific and technological service resource providing and acquiring module 4 is used for acquiring a providing type Stype corresponding to a requirement type Ptype published by each scientific and technological service resource in a scientific and technological service resource set S corresponding to an enterprise user one by one, a plurality of digital providing service quality common attributes SQ corresponding to a plurality of literal requirement service quality common attributes PQ and digital providing service quality special attributes SQ corresponding to the literal requirement service quality special attributes PQ, and combining the plurality of digital providing service quality common attributes SQ and the digital providing service quality special attributes SQ to construct a providing service quality attribute index SQoS.
Specifically, the provision type Stype corresponding to the requirement type Ptype published by each scientific and technical service resource may be "Invention authorization, patent service, invention disclosure, utility model, etc. As shown in Table 3, some scientific and technological service resources S are given i The provided plurality of digital provided quality of service common attributes SQ and the digital provided quality of service special attribute SQ.
TABLE 3 quality of service provided by partial scientific and technical service resources Si
The provided quality of service common attribute SQ is an attribute that each scientific and technological service resource possesses, such as availability, reliability, and cost performance in table 3. The availability is the number of times that the service is browsed and used, the reliability is the probability that the service does not fail, and the cost performance is the probability that the quoted price of the service accounts for the total service. The special attribute SQ of the provided service quality is a unique attribute that is possessed by each technical service resource and can reflect the service quality, such as the special value degree in table 3. The patent merit degree is an evaluation total value for the patent.
Availability SQ in Table 3 above 1 And the commercial PQ in Table 2 1 Corresponding to the reliability SQ in Table 3 2 With stability PQ in Table 2 2 Corresponding cost performance SQ in Table 3 3 And purchasing power PQ in Table 2 3 Corresponding patent merit SQ in Table 3 11 And the patent value PQ in Table 2 11 And correspondingly.
Specifically, the SQoS index is expressed as SQoS,
SQoS＝{SQ 1 ,SQ 2 ，SQ 3 ,……∣SQ n }
SQ 1 issuing PQ for each science and technology service resource in science and technology service resource set S 1 The corresponding quality of service offered common attributes, such as availability in table 3,
SQ 2 issuing PQ for each science and technology service resource in science and technology service resource set S 2 Corresponding quality of service common attributes, e.g. reliability in Table 3，
SQ 3 Issuing PQ for each science and technology service resource in science and technology service resource set S 3 Corresponding quality of service offered common attributes, such as cost/performance ratio in table 3,
SQ n issuing PQ for each science and technology service resource in science and technology service resource set S n Corresponding quality of service provided common attributes such as patent worthiness in table 3.
The enterprise user demand and science and technology service resource matching module 5 comprises a demand service type matching module 5-1, a demand service quality matching module 5-2 and a comprehensive matching module 5-3.
The demand service type matching module 5-1 is configured to perform type matching similarity Simt calculation on the demand type Ptype and the provided type of each scientific and technological service resource in the scientific and technological service resource set S corresponding to the enterprise user one to one, screen out the scientific and technological service resource data that does not match the demand type Ptype, and retain the remaining scientific and technological service resource data that matches the demand type Ptype to form a candidate service resource set corresponding to the enterprise user one to one.
The type matching similarity Simt is calculated specifically as,
in the formula (I), the compound is shown in the specification,
if Simt is 0 or other, indicating that the requirement type Ptype is not matched with the provision type, then screening out the scientific and technological service resource data in the corresponding scientific and technological service resource set S that is not matched with the requirement type Ptype, for example, the requirement type Ptype "invention authorization" is in a Mismatch relationship with the provision type "invention disclosure" and "utility model", so Simt is 0;
if Simt is 1, which means that the requirement type Ptype matches with the provision type, the scientific and technological service resource data matching with the requirement type Ptype in the corresponding scientific and technological service resource set S is retained, for example, the requirement type Ptype "invention authorization" and the provision type Stype "invention authorization" are in Exact relationship, so Simt is 1; the requirement type Ptype "invention grant" and the provision type Stype "patent service" are in a plug relationship, so Simt is 1.
Specifically, in the 12764 available intellectual property service resources, Simt is equal to 0 or other scientific and technical service resources are removed, and the service set composed of 553 service resources, which is equal to 1, is moved to the next candidate service resource set for matching.
The required service quality matching module 5-2 is used for normalizing the original attribute values corresponding to the digital required service quality common attribute PQ and the digital required service quality special attribute PQ in the required service quality attribute index PQoS to obtain a required service quality attribute value vector P' QoS; meanwhile, in a candidate service resource set corresponding to the enterprise users one by one, normalization processing is carried out on a digital service quality providing common attribute SQ and a digital service quality providing special attribute SQ in a service quality providing attribute index SQoS of each scientific and technical service resource to obtain a service quality providing attribute value vector S' QoS; performing service quality similarity Simq calculation on the required service quality attribute value vector P 'QoS and the provided service quality attribute value vector S' QoS to determine a service quality matching similarity threshold; screening out scientific and technological service resource data with the service quality similarity Simq smaller than the service quality matching similarity threshold, reserving the remaining scientific and technological service resource data with the service quality similarity Simq larger than or equal to the service quality matching similarity threshold, and forming a selected service resource set corresponding to the enterprise users one by one.
The specific way of normalizing the digital demand service quality common attribute PQ in the demand service quality attribute index PQoS, the original attribute value corresponding to the digital demand service quality special attribute PQ, or the normalization processing of the digital service quality common attribute SQ and the original attribute value corresponding to the digital service quality special attribute SQ in the service quality attribute index SQoS is that
Wherein, the first and the second end of the pipe are connected with each other,
(1) the formula is a reverse attribute value, and the smaller the reverse attribute value, the better, such as price and service time,
(2) the expression is a forward attribute value, the larger the value of the forward attribute is, the better, such as reliability and credibility,
D' QoSij the normalized attribute value corresponding to the jth attribute of the ith enterprise user in the enterprise user demander set P or the ith candidate service resource in the corresponding candidate service resource set is represented,
D QoSij representing the original attribute value corresponding to the jth attribute of the ith enterprise user in the enterprise user demander set P or the ith candidate service resource in the corresponding candidate service resource set,
D QoSj max represents the maximum value of the original attribute value corresponding to the jth attribute of each enterprise user in the enterprise user demand side set P or each candidate service resource in the corresponding candidate service resource set,
D QoSj min and the minimum value of the original attribute value corresponding to the jth attribute of each enterprise user in the enterprise user demand party set P or each candidate service resource in the corresponding candidate service resource set is represented.
The calculation of the service quality similarity Simq is specifically,
in the formula (I), the compound is shown in the specification,
p ' QoS is a demand quality of service attribute value vector of each enterprise user in the enterprise user demand side set P, and P ' QoS is { P ' QoS1 ,P' QoS2 ,P' QoS3 ,……∣P' QoSn },
P' QoS1 Tongue-and-groove1 st demanded quality of service common attribute PQ of each enterprise user in business user demand party set P 1 The value of the corresponding normalized property is,
P' QoS2 quality of service common attribute PQ for 2 nd requirement of each enterprise user in enterprise user demander set P 2 The value of the corresponding normalized property is,
P' QoS3 quality of service common attribute PQ for 3 rd requirement of each enterprise user in enterprise user demander set P 3 The value of the corresponding normalized property is,
P' QoSn the special attribute PQ of the required service quality is provided for each enterprise user in the enterprise user demand party set P aiming at the scientific and technological service resource type of each requirement n The value of the corresponding normalized property is,
s ' QoS is a provided quality of service attribute value vector of each scientific and technical service resource in the corresponding candidate service resource set, and S ' QoS is { S ' QoS1 ,S' QoS2 ,S' QoS3 ,……∣S' QoSn },
S' QoS1 Providing a quality of service common attribute SQ for the 1 st of the scientific and technical service resources in the corresponding candidate service resource set 1 The value of the corresponding normalized property is,
S' QoS2 providing a service quality common attribute SQ for the 2 nd of each scientific and technical service resource in the corresponding candidate service resource set 2 The value of the corresponding normalized property is,
S' QoS3 providing a service quality common attribute SQ for the 3 rd of each scientific and technical service resource in the corresponding candidate service resource set 3 The value of the corresponding normalized property is,
S' QoSn providing quality of service special attributes SQ for each scientific and technical service resource in corresponding candidate service resource set n The value of the corresponding normalized property is,
simq is the service quality similarity between the required quality of service attribute value vector P 'QoS of each enterprise user in the enterprise user demander set P and the provided quality of service attribute value vector S' QoS of each scientific and technological service resource in the corresponding candidate service resource set.
Specifically, the qos matching similarity threshold value is 0.8, scientific and technological service resource data with qos similarity Simq less than 0.8 are screened out from the candidate service resource set (553 service resources), and the remaining scientific and technological service resource data with qos similarity Simq greater than or equal to 0.8 are retained to form and select a service resource set.
The comprehensive matching module 5-3 is configured to perform comprehensive weighted similarity calculation on the type matching similarity Simt and the service quality similarity Simq of each scientific and technological service resource in the selected service resource set corresponding to the enterprise user one to one, so as to obtain a comprehensive matching similarity Sim (P, S) of each scientific and technological service resource in the corresponding selected service resource set.
The calculation of the comprehensive weighted similarity is specifically that,
Sim(P，S)＝α×Simt+β×Simq
in the formula (I), the compound is shown in the specification,
sim (P, S) is the comprehensive matching similarity of each scientific and technological service resource in the corresponding selected service resource set,
alpha and beta are weight coefficients of comprehensive matching, and the requirement that alpha + beta is 1, alpha is more than or equal to 0, beta is more than or equal to 0,
simt matches similarity for the type of each scientific and technical service resource in the corresponding set of select service resources,
simq is the service quality similarity of each scientific and technological service resource in the corresponding selected service resource set.
The scientific and technological service resource recommending module 6 is used for comparing the comprehensive matching similarity Sim (P, S) of each scientific and technological service resource in the carefully selected service resource set corresponding to the enterprise users one by one with a comprehensive matching similarity threshold, deleting the scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is smaller than the comprehensive matching similarity threshold, retaining the remaining scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is greater than or equal to the comprehensive matching similarity threshold, performing descending order arrangement according to the numerical value of the comprehensive matching similarity Sim (P, S) to obtain an output result, and pushing the scientific and technological service resource of which the comprehensive matching similarity Sim (P, S) is the largest in the output result to the corresponding enterprise user in the enterprise user demand side set P.
Specifically, the weight coefficients α and β are respectively valued at 0.5, and the comprehensive matching similarity threshold ω is not less than 0.900, and table 4 is obtained by calculation. As shown in table 4, the comprehensive matching similarity Sim (P, S) of the enterprise users Pi and the science and technology service resources Si in the refined service resource set is given.
TABLE 4 Enterprise user P i And science and technology service resource S i Integrated matching similarity of
The comprehensive matching similarity Sim (P, S) in table 4 is sorted in descending order to output the scientific and technological service resources, and the final result sorting result is shown in table 5.
TABLE 5 Enterprise user P i And science and technology service resource S i Is obtained by matching
| Outputting the result | |
| P 1 | S 28 >S 31 >S 32 >S 36 >S 27 >S 29 |
| P 2 | S 32 >S 4 >S 6 >S 15 >S 17 >S 8 >S 21 >S 33 >S 13 >S 31 >S 36 >S 14 >S 18 >S 5 >S 10 |
| P 3 | S 32 >S 31 >S 28 >S 36 >S 6 >S 4 >S 33 >S 8 >S 17 >S 15 |
The results are output according to table 5, and the scientific and technological service resource results meeting the requirements of the enterprise users are obtained as follows: enterprise user P 1 Recommending scientific and technological service resources S 28 Enterprise user P 2 Recommending scientific and technological service resources S 32 Enterprise user P 3 Recommending scientific and technological service resources S 32 。
The scientific and technological service resource recommendation system based on the enterprise user requirements can effectively and accurately reflect the degree of the requirement of the enterprise user on the service quality, accurately match the requirement of the enterprise user with the provided scientific and technological service resources, and recommend the optimal scientific and technological service resources to the enterprise user according to the requirement of the enterprise user.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. A scientific and technological service resource recommendation system based on enterprise user requirements is characterized in that: the system comprises a data acquisition module (1), a set generation module (2), an enterprise user demand acquisition module (3), a scientific and technological service resource providing acquisition module (4), an enterprise user demand and scientific and technological service resource matching module (5) and a scientific and technological service resource recommendation module (6); wherein, the first and the second end of the pipe are connected with each other,
the data acquisition module (1) is used for acquiring an enterprise user list, scientific and technological service demand details and service quality requirements issued by an enterprise user demander on a scientific and technological service platform and acquiring scientific and technological service resource data issued by a service resource provider on the scientific and technological service platform;
the set generation module (2) is used for collecting an enterprise user list with requirements on scientific and technological service resources on the scientific and technological service platform to form an enterprise user demand party set P; collecting scientific and technological service resources of corresponding categories for each enterprise user on the scientific and technological service platform according to the respective required scientific and technological service resource categories of each enterprise user in the enterprise user demand side set P to form a scientific and technological service resource set S which corresponds to the enterprise users one by one;
the enterprise user demand acquisition module (3) is used for acquiring a demand type Ptype, a plurality of literal demand service quality common attributes PQ and a literal demand service quality special attribute PQ which are provided by each enterprise user in the enterprise user demand side set P aiming at the scientific and technological service resource category of respective demand, and combining the plurality of literal demand service quality common attributes PQ and the literal demand service quality special attributes PQ to construct a demand service quality attribute index PQoS; performing corresponding literal grade evaluation on a plurality of literal required service quality common attributes PQ in a required service quality attribute index PQoS, then performing fuzzy quantization on the corresponding literal grade evaluation, and performing corresponding range quantization on the literal required service quality special attribute PQ in the required service quality attribute index PQoS, thereby obtaining a digital required service quality common attribute PQ and a digital required service quality special attribute PQ;
the technical service resource providing and acquiring module (4) is used for acquiring a providing type Stype corresponding to a demand type Ptype issued by each technical service resource in a technical service resource set S corresponding to an enterprise user one by one, a plurality of digital providing service quality common attributes SQ corresponding to a plurality of literal demand service quality common attributes PQ and digital providing service quality special attributes SQ corresponding to the literal demand service quality special attributes PQ, and combining the plurality of digital providing service quality common attributes SQ and the digital providing service quality special attributes SQ to construct a providing service quality attribute index SQoS;
the enterprise user demand and science and technology service resource matching module (5) comprises a demand service type matching module (5-1), a demand service quality matching module (5-2) and a comprehensive matching module (5-3);
the demand service type matching module (5-1) is used for carrying out type matching similarity Simt calculation on the demand type Ptype and the provided type Stype of each scientific and technological service resource in the scientific and technological service resource set S corresponding to the enterprise users one by one, screening out scientific and technological service resource data unmatched with the demand type Ptype, reserving the residual scientific and technological service resource data matched with the demand type Ptype, and forming a candidate service resource set corresponding to the enterprise users one by one;
the demand service quality matching module (5-2) is used for carrying out normalization processing on original attribute values corresponding to a digital demand service quality common attribute PQ and a digital demand service quality special attribute PQ in a demand service quality attribute index PQoS to obtain a demand service quality attribute value vector P' QoS; meanwhile, in a candidate service resource set corresponding to enterprise users one by one, normalizing a common attribute SQ of digital service quality provided in a service quality providing attribute index SQoS of each scientific and technical service resource and an original attribute value corresponding to a special attribute SQ of digital service quality provided to obtain a service quality providing attribute value vector S' QoS; performing service quality similarity Simq calculation on the required service quality attribute value vector P 'QoS and the provided service quality attribute value vector S' QoS to determine a service quality matching similarity threshold; screening out scientific and technological service resource data with the service quality similarity Simq smaller than the service quality matching similarity threshold, and reserving the rest scientific and technological service resource data with the service quality similarity Simq larger than or equal to the service quality matching similarity threshold to form a selected service resource set corresponding to the enterprise users one by one;
the comprehensive matching module (5-3) is used for carrying out comprehensive weighted similarity calculation on the type matching similarity Simt and the service quality similarity Simq of each scientific and technological service resource in the selected service resource set corresponding to the enterprise user one by one to obtain the comprehensive matching similarity Sim (P, S) of each scientific and technological service resource in the corresponding selected service resource set;
the scientific and technological service resource recommending module (6) is used for comparing the comprehensive matching similarity Sim (P, S) of all scientific and technological service resources in the carefully selected service resource set corresponding to the enterprise users one by one with a comprehensive matching similarity threshold, deleting the scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is smaller than the comprehensive matching similarity threshold, reserving the remaining scientific and technological service resource data of which the comprehensive matching similarity Sim (P, S) is larger than or equal to the comprehensive matching similarity threshold, performing descending order according to the numerical value of the comprehensive matching similarity Sim (P, S) to obtain an output result, and pushing the scientific and technological service resource with the maximum numerical value of the comprehensive matching similarity Sim (P, S) in the output result to the corresponding enterprise user in the enterprise user demand side set P.
2. The system of claim 1, wherein the system comprises: in the enterprise user demand acquisition module (3), the demand quality of service attribute index PQoS is expressed as,
PQoS＝{PQ 1 ,PQ 2 ,PQ 3 ,……∣PQ n }
in the formula (I), the compound is shown in the specification,
PQ 1 the 1 st required quality of service common attribute is provided for each enterprise user in the enterprise user demander set P,
PQ 2 the 2 nd demanded quality of service common attribute is proposed for each enterprise user in the enterprise user demander set P,
PQ 3 the 3 rd required quality of service common attribute is proposed for each enterprise user in the enterprise user demander set P,
PQ n and providing special attribute of required service quality for each enterprise user in the enterprise user demand side set P.
3. The system of claim 2, wherein the system comprises: in the enterprise user requirement acquisition module (3), a method for fuzzy quantification of the textural grade evaluation is to adopt a triangular fuzzy evaluation method, and the triangular fuzzy evaluation method specifically comprises the following steps: the evaluation of the degree of the literary property is divided into seven degree grades of 'very low', 'low medium', 'medium low', 'medium', 'high', 'very high', each degree grade is quantified through a respective matched membership equation, and a quantified value is represented by a triangular fuzzy number M (l, M, u), wherein l is less than or equal to M and less than or equal to u, l and u respectively represent a lower boundary and an upper boundary of M, M is a median of M, and M (l, M, u) represents a deviation degree of M relative to M.
4. A scientific and technological service resource recommendation system based on enterprise user demand according to claim 3, characterized in that: in the scientific and technological service resource providing and obtaining module (4), the quality of service attribute index SQoS is represented as,
SQoS＝{SQ 1 ,SQ 2 ，SQ 3 ,……∣SQ n }
SQ 1 issuing PQ for each science and technology service resource in science and technology service resource set S 1 The corresponding quality of service offered common attributes,
SQ 2 issuing PQ for each science and technology service resource in science and technology service resource set S 2 A corresponding quality of service provision common attribute,
SQ 3 issuing PQ for each science and technology service resource in science and technology service resource set S 3 The corresponding quality of service offered common attributes,
SQ n issuing PQ for each science and technology service resource in science and technology service resource set S n Corresponding quality of service provided common attributes.
5. The system of claim 4, wherein the system comprises: in the demand service type matching module (5-1), the calculation of the type matching similarity Simt is specifically
In the formula (I), the compound is shown in the specification,
if Simt is 0 or other, which indicates that the requirement type Ptype is not matched with the provision type Stype, then screening out the scientific and technological service resource data in the corresponding scientific and technological service resource set S that are not matched with the requirement type Ptype;
if Simt is 1, indicating that the requirement type Ptype matches the provision type Stype, the scientific and technical resource data matching the requirement type Ptype in the corresponding scientific and technical resource set S is reserved.
6. The system of claim 5, wherein the system comprises: in the required service quality matching module (5-2), the specific way of normalizing the digital required service quality common attribute PQ in the required service quality attribute index PQoS and the original attribute value corresponding to the digital required service quality special attribute PQ, or normalizing the digital provided service quality common attribute SQ in the provided service quality attribute index SQoS and the original attribute value corresponding to the digital provided service quality special attribute SQ in the provided service quality attribute index SQoS is that
Wherein the content of the first and second substances,
(1) the formula is a reverse attribute value, such as price, service time,
(2) the formula is a forward attribute value, such as reliability and credibility,
D' QoSij the normalized attribute value corresponding to the jth attribute of the ith enterprise user in the enterprise user demander set P or the ith candidate service resource in the corresponding candidate service resource set is represented,
D QoSij representing the ith enterprise in an enterprise user demander set PThe original attribute value corresponding to the j attribute of the ith candidate service resource in the business user or the corresponding candidate service resource set,
D QoSj max represents the maximum value of the original attribute value corresponding to the jth attribute of each enterprise user in the enterprise user demand side set P or each candidate service resource in the corresponding candidate service resource set,
D QoSj min and the minimum value of the original attribute value corresponding to the jth attribute of each enterprise user in the enterprise user demand party set P or each candidate service resource in the corresponding candidate service resource set is represented.
7. The system of claim 6, wherein the system comprises: in the required service quality matching module (5-2), the service quality similarity Simq is specifically calculated as,
in the formula (I), the compound is shown in the specification,
p ' QoS is a vector of demanded quality of service attribute values for each enterprise user in the set of enterprise user demands P, P ' QoS ═ P ' QoS1 ,P' QoS2 ,P' QoS3 ,……∣P' QoSn },
P' QoS1 Quality of service common attribute PQ for 1 st requirement of each enterprise user in enterprise user demander set P 1 The value of the corresponding normalized property is,
P' QoS2 quality of service common attribute PQ for 2 nd requirement of each enterprise user in enterprise user demander set P 2 The value of the corresponding normalized property is,
P' QoS3 quality of service common attribute PQ for 3 rd requirement of each enterprise user in enterprise user demander set P 3 The value of the corresponding normalized property is,
P' QoSn science and technology for each enterprise user in enterprise user demander set P according to respective requirementsPQ (quality of service) special attribute required by service resource class n The value of the corresponding normalized property is,
s ' QoS is a provided quality of service attribute value vector of each scientific and technical service resource in the corresponding candidate service resource set, and S ' QoS is { S ' QoS1 ,S' QoS2 ,S' QoS3 ,……∣S' QoSn },
S' QoS1 Providing a service quality common attribute SQ for the 1 st of the science and technology service resources in the corresponding candidate service resource set 1 The value of the corresponding normalized property is,
S' QoS2 providing a service quality common attribute SQ for the 2 nd of each scientific and technical service resource in the corresponding candidate service resource set 2 The value of the corresponding normalized property is,
S' QoS3 providing a service quality common attribute SQ for the 3 rd of each scientific and technical service resource in the corresponding candidate service resource set 3 The value of the corresponding normalized property is,
S' QoSn providing quality of service special attributes SQ for each scientific and technical service resource in corresponding candidate service resource set n The value of the corresponding normalized property is,
simq is the service quality similarity between the required quality of service attribute value vector P 'QoS of each enterprise user in the enterprise user demander set P and the provided quality of service attribute value vector S' QoS of each scientific and technological service resource in the corresponding candidate service resource set.
8. The system of claim 7, wherein the system comprises: in the comprehensive matching module (5-3), the comprehensive weighted similarity calculation is specifically,
Sim(P，S)＝α×Simt+β×Simq
in the formula (I), the compound is shown in the specification,
sim (P, S) is the comprehensive matching similarity of each scientific and technological service resource in the corresponding selected service resource set,
alpha and beta are weight coefficients of comprehensive matching, and the requirement that alpha + beta is 1, alpha is more than or equal to 0, beta is more than or equal to 0,
simt matches similarity for the type of each scientific and technical service resource in the corresponding set of select service resources,
simq is the service quality similarity of each scientific and technological service resource in the corresponding selected service resource set.
9. The system of claim 8, wherein the system comprises: in the required service quality matching module (5-2), the service quality matching similarity threshold value takes 0.8; in the scientific and technological service resource recommendation module (6), the comprehensive matching similarity threshold is 0.9.
10. The system of claim 1, wherein the system comprises: in the set generation module (2), the scientific and technological service resource categories comprise scientific and technological popularization, scientific and technological consultation, inspection and detection, scientific and technological finance, research and development, entrepreneurship incubation, technical transfer and intellectual property rights; the special attributes of scientific and technological popularization, scientific and technological consultation, inspection and detection, scientific and technological finance, research and development, entrepreneurship incubation, technical transfer and intellectual property rights are respectively science popularization expenditure, effective consultation rate, effective detection result rate, total financing amount, development service amount, incubation enterprise number, technical talent amount and patent value degree.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210517702.1A CN114969518B (en) | 2022-05-12 | 2022-05-12 | Scientific and technological service resource recommendation system based on enterprise user demands |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210517702.1A CN114969518B (en) | 2022-05-12 | 2022-05-12 | Scientific and technological service resource recommendation system based on enterprise user demands |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114969518A true CN114969518A (en) | 2022-08-30 |
| CN114969518B CN114969518B (en) | 2024-06-14 |
Family
ID=82983923
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210517702.1A Active CN114969518B (en) | 2022-05-12 | 2022-05-12 | Scientific and technological service resource recommendation system based on enterprise user demands |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114969518B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116308170A (en) * | 2023-03-21 | 2023-06-23 | 北京中关村软件园孵化服务有限公司 | Management method and system applied to digital hatching service platform |
| CN116720896A (en) * | 2023-08-10 | 2023-09-08 | 青岛阿斯顿工程技术转移有限公司 | Enterprise scientific and technological service personalized recommendation method and system based on big data |
| CN116956857A (en) * | 2023-06-28 | 2023-10-27 | 中国人民解放军63921部队 | Design method and design system for test task data acquisition scheme |
| JP7382590B1 (en) | 2023-02-21 | 2023-11-17 | リンカーズ株式会社 | Information processing device, information processing method and program |
| CN117150138A (en) * | 2023-09-12 | 2023-12-01 | 广东省华南技术转移中心有限公司 | Scientific and technological resource organization method and system based on high-dimensional space mapping |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040024717A1 (en) * | 1998-04-03 | 2004-02-05 | Enerwise Global Technologies, Inc. | Computer assisted and/or implemented process and architecture for web-based monitoring of energy related usage, and client accessibility therefor |
| CN111210307A (en) * | 2020-01-03 | 2020-05-29 | 武汉理工大学 | Scientific and technological service chain intelligent recommendation system and method with response user preference as core |
| CN113806410A (en) * | 2021-08-30 | 2021-12-17 | 上海大学 | Service recommendation experiment system for scientific and technological service |
| CN114429043A (en) * | 2022-01-18 | 2022-05-03 | 武汉理工大学 | Organization recommendation system and method based on scientific and technological service requirements |
-
2022
- 2022-05-12 CN CN202210517702.1A patent/CN114969518B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040024717A1 (en) * | 1998-04-03 | 2004-02-05 | Enerwise Global Technologies, Inc. | Computer assisted and/or implemented process and architecture for web-based monitoring of energy related usage, and client accessibility therefor |
| CN111210307A (en) * | 2020-01-03 | 2020-05-29 | 武汉理工大学 | Scientific and technological service chain intelligent recommendation system and method with response user preference as core |
| CN113806410A (en) * | 2021-08-30 | 2021-12-17 | 上海大学 | Service recommendation experiment system for scientific and technological service |
| CN114429043A (en) * | 2022-01-18 | 2022-05-03 | 武汉理工大学 | Organization recommendation system and method based on scientific and technological service requirements |
Non-Patent Citations (1)
| Title |
|---|
| 杨静;杨代庆;: "典型科技资源共享平台服务模式对比分析", 中国科技资源导刊, no. 01, 28 January 2020 (2020-01-28) * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7382590B1 (en) | 2023-02-21 | 2023-11-17 | リンカーズ株式会社 | Information processing device, information processing method and program |
| CN116308170A (en) * | 2023-03-21 | 2023-06-23 | 北京中关村软件园孵化服务有限公司 | Management method and system applied to digital hatching service platform |
| CN116308170B (en) * | 2023-03-21 | 2023-10-13 | 北京中关村软件园孵化服务有限公司 | Management method and system applied to digital hatching service platform |
| CN116956857A (en) * | 2023-06-28 | 2023-10-27 | 中国人民解放军63921部队 | Design method and design system for test task data acquisition scheme |
| CN116956857B (en) * | 2023-06-28 | 2024-01-26 | 中国人民解放军63921部队 | Design method and design system for test task data acquisition scheme |
| CN116720896A (en) * | 2023-08-10 | 2023-09-08 | 青岛阿斯顿工程技术转移有限公司 | Enterprise scientific and technological service personalized recommendation method and system based on big data |
| CN116720896B (en) * | 2023-08-10 | 2023-10-24 | 青岛阿斯顿工程技术转移有限公司 | Enterprise scientific and technological service personalized recommendation method and system based on big data |
| CN117150138A (en) * | 2023-09-12 | 2023-12-01 | 广东省华南技术转移中心有限公司 | Scientific and technological resource organization method and system based on high-dimensional space mapping |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114969518B (en) | 2024-06-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114969518A (en) | Scientific and technological service resource recommendation system based on enterprise user requirements | |
| CN109783639B (en) | Mediated case intelligent dispatching method and system based on feature extraction | |
| CN111160992A (en) | Marketing system based on user portrait system | |
| CN109255586B (en) | Online personalized recommendation method for e-government affairs handling | |
| CN103761254B (en) | Method for matching and recommending service themes in various fields | |
| CN110704572A (en) | Suspected illegal fundraising risk early warning method, device, equipment and storage medium | |
| CN112102073A (en) | Credit risk control method and system, electronic device and readable storage medium | |
| Vysotska et al. | The commercial content digest formation and distributional process | |
| CN108595525A (en) | A kind of lawyer's information processing method and system | |
| CN111738819A (en) | Method, device and equipment for screening characterization data | |
| CN117151870B (en) | Portrait behavior analysis method and system based on guest group | |
| CN109063171B (en) | Resource matching method based on semantics | |
| CN113159881B (en) | Data clustering and B2B platform customer preference obtaining method and system | |
| CN108681548A (en) | A kind of lawyer's information processing method and system | |
| Lukosius et al. | Marketing theory and big data | |
| CN111583012A (en) | Method for evaluating default risk of credit, debt and debt main body by fusing text information | |
| CN107239964A (en) | User is worth methods of marking and system | |
| CN105786810B (en) | The method for building up and device of classification mapping relations | |
| CN112328868A (en) | Credit evaluation and credit granting application system and method based on information data | |
| Shiri Daryani et al. | Inverse DEA in two-stage systems based on allocative efficiency | |
| CN112417280A (en) | Recommendation method and system based on virtual reality moderator system | |
| Chen et al. | Using data mining to provide recommendation service | |
| Kong et al. | Skill ranking of researchers via hypergraph | |
| Huang et al. | An algorithm for calculating process similarity to cluster open-source process designs | |
| CN114897607A (en) | Data processing method and device for product resources, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |