CN104867033A - Electronic commerce client evaluation judging and marking system - Google Patents

Electronic commerce client evaluation judging and marking system Download PDF

Info

Publication number
CN104867033A
CN104867033A CN201510251202.8A CN201510251202A CN104867033A CN 104867033 A CN104867033 A CN 104867033A CN 201510251202 A CN201510251202 A CN 201510251202A CN 104867033 A CN104867033 A CN 104867033A
Authority
CN
China
Prior art keywords
evaluation
judge
similarity
judge module
false
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.)
Pending
Application number
CN201510251202.8A
Other languages
Chinese (zh)
Inventor
吴雨浓
何宏靖
刘世林
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chengdu Business Big Data Technology Co Ltd
Original Assignee
Chengdu Business Big Data Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Chengdu Business Big Data Technology Co Ltd filed Critical Chengdu Business Big Data Technology Co Ltd
Priority to CN201510251202.8A priority Critical patent/CN104867033A/en
Publication of CN104867033A publication Critical patent/CN104867033A/en
Pending legal-status Critical Current

Links

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to the internet field, and especially relates to an electronic commerce client evaluation judging and marking system. The system comprises a client, a network connection device, an ID similarity judgment module, a content similarity judgment module and a false evaluation marking module. The client acquires relevant evaluation data information of a target commodity through the network connection device, and outputs the information to the ID similarity judgment module, the content similarity judgment module and the false evaluation marking module which are sequentially connected. Based on an ID similarity analysis of target commodity evaluations, the system determines whether evaluation content given by the same or similar evaluation IDs are the same or similar through the content similarity judgment module; if the evaluation content is the same or similar, the system determines that the IDs giving the same or similar evaluations are the false evaluation IDs; and the system timely marks the false evaluation IDs and the corresponding evaluations through the false evaluation marking module. The system can automatically indentify the false evaluations from the target commodity evaluations.

Description

Ecommerce customer evaluation judge mark system
Technical field
The present invention relates to internet arena, particularly ecommerce customer evaluation judge mark system.
Background technology
In the present age, along with popularizing of internet, ecommerce has become a kind of commerce and trade mode be widely used.Both parties mainly carry out transaction by the webpage of electric business or software.Because ecommerce does not have traditional entity StoreFront, not high to the quantitative requirement of sales force yet, so compare conventional transaction pattern more can control operation cost, thus there is larger price advantage.But, have a lot of illegal businessman to improve the sales volume of oneself thus employing specialty brush to evaluate team also to manufacture a large amount of false evaluation and carry out false publication to the commodity of oneself, thus deception consumer improves the true sales volume of oneself.
The development of current ecommerce is swift and violent, the scale of construction is huge, Seller Number in electricity quotient ring border is numerous, user is difficult to when carrying out purchase decision the authenticity judging descriptive labelling, the dependency degree evaluated commodity is very high, the performance favorable comment degree virtual height of commodity caused because seller evaluates cheating and the situation of buyer's interests loss that causes is serious.Under these circumstances, how the evaluation cheating of businessman in ecommerce identified and judge into problem demanding prompt solution in e-commerce development process; Judge the accuracy how improving judgement in false evaluation process, avoid the generation of erroneous judgement situation to be also very important considerations; The judgement that relevant device accurately and effectively realizes being correlated with also is lacked in currently available technology.
Summary of the invention
In order to solve problems of the prior art, the invention provides ecommerce customer evaluation judge mark system, being identified the identical and similar evaluation ID in end article evaluating data by ID similarity judge module; And by content similarities judge module on the basis judging identical and similar ID, identify these identical or similar evaluation content evaluated given by ID whether identical and similar, when commodity evaluation content corresponding to these ID also identical or similar time, then these ID can be judged as false evaluation ID, and then judge a large amount of false evaluation given by professional brush evaluation personnel; And the false ID judged by content similarities judge module and corresponding evaluation content are also marked by false evaluation mark module by this ecommerce customer evaluation judge mark system, achieve the automatic identification of false evaluation in end article evaluation like this, for electric business environment administrator and commodity consumption person provide simple and reliable evaluation identification instrument.
In order to realize foregoing invention object, the invention provides following technical scheme:
Ecommerce customer evaluation judge mark system; Comprise client computer, network connection device, ID similarity judge module, content similarities judge module and false evaluation mark module; The relevant evaluation data message that wherein said client computer one end obtains end article by network connection device (can get the relevant information in target web at present very easily by crawler technology, the speed extracted is fast, the total amount can analyzing data is huge, to extract the analytical approach of data ripe, with low cost); The other end of described client computer is connected with the input end of described ID similarity judge module, and the output terminal of described ID similarity judge module is connected with the input end of described content similarities judge module.The end article evaluation information got outputs in described ID similarity judge module by described client computer, whether by text similarity, described ID similarity judge module judges that these evaluate ID identical or similar, and will judge that result (identical or similar ID) is input in content similarities judge module; If the evaluation content that these ID send is also a large amount of identical or similar, these ID are then judged as false evaluation ID by described content similarities judge module.
If businessman wants by wash sale and evaluates the sales volume and the favorable comment situation that improve system display of commodity at present, the quantity of required false evaluation is comparatively large, under these circumstances; Occupation brush evaluation team manually or can utilize automatic register machine, and to register a lot of trumpet, (so-called trumpet refers to, same person registration and different No. ID of using), the small size ID that these vocational evaluation team register and use has certain regularity; Generally vocational evaluation teacher register a series of No. ID also according to system recommendation or automatically generate, such mode No. ID of producing can have larger relevance and similarity, such as ABC1, ABC2, ABC3, ABC4, ABC5....ABCn.By identical or similar evaluation ID relatively just can be judged to the text similarity evaluating ID; If ID is identical or similar, so these ID are that the possibility of false ID is very high.
In order to improve the accuracy that false evaluation judges further, make the result of judgement more strict, judged result is input in described content similarities judge module by described ID similarity judge module; Described content similarities judge module, on the basis of the identical or similar ID judged, analyzes the content that corresponding ID sends evaluation, judges that whether the evaluation content that these ID send is identical or similar.When needing a large amount of evaluation, people is that the evaluation of fabricating often also has higher similarity in evaluation content, or occur with identical content with regard to direct, content similarities judge module in the present invention is by the similarity (determination methods that current text similarity compares the comparative maturity of the content text in comparison object commodity evaluating data, such as the similarity degree that cosine ratio of similitude can be taked comparatively to judge between content of text, when similarity degree exceedes default threshold value, then can think similar by the content of text compared, concrete comparison procedure repeats no more), the quantity of the identical evaluation of statistical content, judge the evaluation that content is similar, and count the quantity of the similar evaluation of content, calculate the likelihood of evaluation content to be compared, compared by the threshold value that similar Assessment Rate result of calculation and module are pre-set, if this similar Assessment Rate exceedes threshold value, then evaluation content to be compared is judged as similar evaluation.By native system judge that the process of false evaluation is strict, judged result accuracy is high.
Preferred as one, described ID similarity judge module is that ID similarity judges server; Described content similarities judge module is that content similarities judges server.Described similar evaluation content judges server, ID similarity judges that server and content similarities judge that server is connected successively by data connecting line.Server is exhibits excellent in processing power, stability, reliability, security, extensibility, manageability etc., relevant ID similarity is completed by server, the correlated judgment of content similarities, can the related data of a large amount of electric business's end article of fast processing, processing speed is fast, and efficiency is high.
Further, described content similarities judge module is also connected with false evaluation mark module by data connecting line.Described false evaluation mark module is false evaluation mark server, and the false evaluation judged is marked according to the Output rusults of described content similarities judge module by described false evaluation mark module.The present invention carries out scientific analysis to the authenticity of the evaluation of end article and reasonably judges, the false evaluation identified in end article evaluation is (high to the discriminating accuracy rate of a large amount of false evaluation given by occupation brush evaluation team, there is stronger specific aim), and by the mark to false evaluation, intuitively the non-honest behavior that the evaluation of electric business is practised fraud is shown in face of commodity buyer and electric business supvr; Be conducive to the purification of e-commerce environment, maintain the rational interests of commodity purchaser and sincere seller, improve the confidence level of businessman's prestige; Contribute to the sound development of electric firm industry.
Compared with prior art, beneficial effect of the present invention: the invention provides ecommerce customer evaluation judge mark system.By the network address of client access end article, crawl the evaluating data of corresponding goods webpage, and by server, the evaluating data crawled is judged, evaluation content in assay data, described similar ID judges server, evaluation ID is analyzed, counted the quantity of identical ID by text similarity algorithm, and judge the likelihood probability of other ID, evaluation ID similar threshold value likelihood probability and machine learning drawn compares, determine similar evaluation ID, and add up the judged result of similar ID, on the basis judging identical and similar ID, by described content similarities judge module, the similarity of the evaluation content that Target id sends is judged, determine that these identical or similar ID are the possibility of false ID, if the evaluation content corresponding to these criticisms ID is also identical or similar, these is evaluated ID and is judged as false evaluation ID, eventually through false evaluation mark module, the false evaluation related content judged and ID are marked, electric business's customer evaluation identification system of the present invention has carried out similar ID identification targetedly to the trumpet that vocational evaluation teacher registers, and in order to improve the judgment accuracy of false evaluation, similarity analysis is carried out to corresponding content in the basis that identical ID judges, improve the accuracy of judgement, the judgement of vocational evaluation teacher evaluation cheating serious is like this engaged to significantly improve to end article, contribute to the confidence level improving electric quotient ring border, be conducive to the formation of normal management and control order.Buyer is helped to evade the transaction risk brought because seller evaluates cheating.
Accompanying drawing illustrates:
Fig. 1 is this ecommerce customer evaluation judge mark system annexation figure.
Fig. 2 is the preferred annexation figure of this ecommerce customer evaluation judge mark system.
Embodiment
Below in conjunction with test example and embodiment, the present invention is described in further detail.But this should be interpreted as that the scope of the above-mentioned theme of the present invention is only limitted to following embodiment, all technology realized based on content of the present invention all belong to scope of the present invention.
The invention provides ecommerce customer evaluation judge mark system, identified the identical and similar evaluation ID in end article evaluating data by ID similarity judge module; And by content similarities judge module on the basis judging identical and similar ID, identify these identical or similar evaluation content evaluated given by ID whether identical and similar, when commodity evaluation content corresponding to these ID also identical or similar time, then these ID can be judged as false evaluation ID, and then judge a large amount of false evaluation given by professional brush evaluation personnel; And the false ID judged by content similarities judge module and corresponding evaluation content are also marked by false evaluation mark module by this ecommerce customer evaluation judge mark system, achieve the automatic identification of false evaluation in end article evaluation like this, for electric business environment administrator and commodity consumption person provide simple and reliable evaluation identification instrument.
In order to realize foregoing invention object, the invention provides following technical scheme:
Ecommerce customer evaluation judge mark system, as shown in Figure 1: comprise client computer, network connection device, ID similarity judge module, content similarities judge module and false evaluation mark module; The relevant evaluation data message that wherein said client computer one end obtains end article by network connection device (can get the relevant information in target web at present very easily by crawler technology, the speed extracted is fast, the total amount can analyzing data is huge, to extract the analytical approach of data ripe, with low cost); The other end of described client computer is connected with the input end of described ID similarity judge module, and the output terminal of described ID similarity judge module is connected with the input end of described content similarities judge module.The end article evaluation information got outputs in described ID similarity judge module by described client computer, whether by text similarity, described ID similarity judge module judges that these evaluate ID identical or similar, and will judge that result (identical or similar ID) is input in content similarities judge module; If the evaluation content that these ID send is also a large amount of identical or similar, these ID are then judged as false evaluation ID by described content similarities judge module.
If businessman wants by wash sale and evaluates the sales volume and the favorable comment situation that improve system display of commodity at present, the quantity of required false evaluation is comparatively large, under these circumstances; Occupation brush evaluation team manually or can utilize automatic register machine, and to register a lot of trumpet, (so-called trumpet refers to, same person registration and different No. ID of using), the small size ID that these vocational evaluation team register and use has certain regularity; Generally vocational evaluation teacher register a series of No. ID also according to system recommendation or automatically generate, such mode No. ID of producing can have larger relevance and similarity, such as ABC1, ABC2, ABC3, ABC4, ABC5....ABCn.By identical or similar evaluation ID relatively just can be judged to the text similarity evaluating ID; If ID is identical or similar, so these ID are that the possibility of false ID is very high.
In order to improve the accuracy that false evaluation judges further, make the result of judgement more strict, judged result is input in described content similarities judge module by described ID similarity judge module; Described content similarities judge module, on the basis of the identical or similar ID judged, analyzes the content that corresponding ID sends evaluation, judges that whether the evaluation content that these ID send is identical or similar.When needing a large amount of evaluation, people is that the evaluation of fabricating often has higher similarity in evaluation content, or occur with identical content with regard to direct, content similarities judge module in the present invention is by the similarity (determination methods that current text similarity compares the comparative maturity of the content text in comparison object commodity evaluating data, such as the similarity degree that cosine ratio of similitude can be taked comparatively to judge between content of text, when similarity degree exceedes default threshold value, then can think similar by the content of text compared, concrete comparison procedure is as follows: in order to the cosine similarity realizing all evaluations calculates, can crawl the overall merit data of certain electric business website in advance, and according to word frequency, after we delete some function words (such as punctuate) and some low-frequency words, establish an effective notional word vocabulary as shown in table 1.
Table 1
In the specific evaluation of a certain bar, (TF-IDF is a kind of statistical method, in order to assess the significance level of a words for a copy of it file in a file set or a corpus to calculate the TF-IDF value of all notional words.The importance of words to be directly proportional increase along with the number of times that it occurs hereof, the decline but the frequency that can occur in corpus along with it is inversely proportional to simultaneously, computing method can with reference to wikipedia http://zh.wikipedia.org/wiki/TF-IDF, repeat no more) herein, a vector is drawn according to their positional alignment in vocabulary, for the word not having to occur, the value of its correspondence is zero, as shown in table 2.
Table 2
Form the vector of a n dimension by the n number calculated, and represent this evaluation with this vector.
Want the cosine similarity of Calculation Estimation A and evaluation B, need to obtain these two vectors evaluating correspondence respectively as follows:
A 1, a 2..., a nand b 1, b 2..., b n
Two likelihood probability P evaluated are to utilize cosine formula to draw
p = cos θ = a 1 b 1 + a 2 b 2 + . . . + a n b n a 1 2 + a 2 2 + . . . + a n 2 · b 1 2 + b 2 2 + . . . + b n 2
Wherein θ represents the angle between two vectors, and probability is larger, represents that two similaritys commented on are larger, otherwise represents that the similarity of two comments is less.The likelihood probability calculated and content similarities threshold value are compared, if be greater than this threshold value, is then judged to be similar comment; The process of choosing of content similarities threshold value is:
A floating number is chosen as threshold value in scope (0.000 ~ 0.999), similar data set has been determined by being manually extracted one, calculate the similar value that data centralization is evaluated between two, the accuracy rate of the highest similar judgement can be obtained when choosing certain threshold value, we just think that this threshold value is best threshold value), the quantity of the identical evaluation of statistical content, judges the evaluation that content is similar, and counts the quantity of the similar evaluation of content; And the evaluation ID of correspondence is judged as the deterministic process that false evaluation ID evaluates the false evaluation given by team by native system to occupation brush is relatively strict, judged result accuracy is high.
Preferred as one, as shown in Figure 2: described ID similarity judge module is that ID similarity judges server; Described content similarities judge module is that content similarities judges server.Described ID similarity judges that server and content similarities judge that server is connected by data connecting line.Server is exhibits excellent in processing power, stability, reliability, security, extensibility, manageability etc., relevant ID similarity is completed by server, the correlated judgment of content similarities, can the related data of a large amount of electric business's end article of fast processing, processing speed is fast, and efficiency is high.
Further, described content similarities judge module is also connected with false evaluation mark module by data connecting line.Described false evaluation mark module is false evaluation mark server, and the false evaluation judged is marked according to the Output rusults of described content similarities judge module by described false evaluation mark module.The present invention carries out scientific analysis to the authenticity of the evaluation of end article and reasonably judges, the false evaluation identified in end article evaluation is (high to the discriminating accuracy rate of a large amount of false evaluation given by occupation brush evaluation team, there is stronger specific aim), and by the mark to false evaluation, intuitively the non-honest behavior that the evaluation of electric business is practised fraud is shown in face of commodity buyer and electric business supvr; Be conducive to the purification of e-commerce environment, maintain the rational interests of commodity purchaser and sincere seller, improve the confidence level of businessman's prestige; Contribute to the sound development of electric firm industry.

Claims (7)

1. ecommerce customer evaluation judge mark system, is characterized in that, comprises client computer, network connection device, ID similarity judge module, content similarities judge module and false evaluation mark module; One end of wherein said client computer obtains the relevant evaluation data message of end article by network connection device, the other end of described client computer is connected with the input end of described ID similarity judge module, the output terminal of described ID similarity judge module is connected with the input end of described content similarities judge module, and the output terminal of described content similarities judge module is connected with the input end of described false evaluation judge module.
2. ecommerce customer evaluation judge mark system as claimed in claim 1, it is characterized in that, the end article evaluation information got outputs in described ID similarity judge module by described client computer; Through text similarity recognition methods, described ID similarity judge module judges that whether these ID are identical or similar, and judged result be input in described content similarities judge module; If wait to judge ID to send the content of evaluation also identical or similar, then these ID are judged as false evaluation ID by described content similarities judge module.
3. ecommerce customer evaluation judge mark system as claimed in claim 2, it is characterized in that, described ID similarity judge module is that ID similarity judges server; Described content similarities judge module is that content similarities judges server; Described false evaluation mark module is false evaluation mark server.
4. ecommerce customer evaluation judge mark system as claimed in claim 3, is characterized in that, described ID similarity judges server, described content similarities judges server and described false evaluation mark server is connected successively by data connecting line.
5. ecommerce customer evaluation judge mark system as claimed in claim 4, it is characterized in that, the false evaluation that described content similarities judge module is judged is marked by described false evaluation mark module.
6. ecommerce customer evaluation judge mark system as claimed in claim 5, is characterized in that described ID similarity judge module, by carrying out text identification to the evaluation ID in evaluating data, counts identical with similar evaluation ID respectively.
7. ecommerce customer evaluation judge mark system as claimed in claim 5, it is characterized in that, described content similarities judge module, on the basis that identical and similar ID judges, by text similarity comparison algorithm, judge identical with similar evaluation content respectively.
CN201510251202.8A 2015-05-16 2015-05-16 Electronic commerce client evaluation judging and marking system Pending CN104867033A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510251202.8A CN104867033A (en) 2015-05-16 2015-05-16 Electronic commerce client evaluation judging and marking system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510251202.8A CN104867033A (en) 2015-05-16 2015-05-16 Electronic commerce client evaluation judging and marking system

Publications (1)

Publication Number Publication Date
CN104867033A true CN104867033A (en) 2015-08-26

Family

ID=53912851

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510251202.8A Pending CN104867033A (en) 2015-05-16 2015-05-16 Electronic commerce client evaluation judging and marking system

Country Status (1)

Country Link
CN (1) CN104867033A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113256372A (en) * 2021-05-14 2021-08-13 深圳迅销科技股份有限公司 Commodity sale system and method based on electronic commerce

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103020482A (en) * 2013-01-05 2013-04-03 南京邮电大学 Relation-based spam comment detection method
CN103778186A (en) * 2013-12-31 2014-05-07 南京财经大学 Method for detecting sockpuppet
CN103984673A (en) * 2013-02-11 2014-08-13 谷歌股份有限公司 Automatic detection of fraudulent ratings/comments related to an application store

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103020482A (en) * 2013-01-05 2013-04-03 南京邮电大学 Relation-based spam comment detection method
CN103984673A (en) * 2013-02-11 2014-08-13 谷歌股份有限公司 Automatic detection of fraudulent ratings/comments related to an application store
CN103778186A (en) * 2013-12-31 2014-05-07 南京财经大学 Method for detecting sockpuppet

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113256372A (en) * 2021-05-14 2021-08-13 深圳迅销科技股份有限公司 Commodity sale system and method based on electronic commerce

Similar Documents

Publication Publication Date Title
CN104867017A (en) Electronic commerce client false evaluation identification system
CN104881796A (en) False comment judgment system based on comment content and ID recognition
TWI787196B (en) Method, device and system for generating business object attribute identification
US20200272917A1 (en) Method, apparatus, and computer program product for determining a provider return rate
CN104881795A (en) E-commerce false comment judging and recognizing method
Peng et al. Detecting Spam Review through Sentiment Analysis.
US10558922B2 (en) Method, apparatus, and computer program product for determining a provider return rate
WO2019061994A1 (en) Electronic device, insurance product recommendation method and system, and computer readable storage medium
US20210035126A1 (en) Data processing method, system and computer device based on electronic payment behaviors
CN105335496A (en) Customer service repeated call treatment method based on cosine similarity text mining algorithm
CN105550227B (en) Named entity identification method and device
JP2012014544A (en) Coordinate recommendation apparatus, coordinate recommendation method and program therefor
CN112860841A (en) Text emotion analysis method, device and equipment and storage medium
CN109118118A (en) Methods of risk assessment, storage medium and the server of business event
CN104867032A (en) Electronic commerce client evaluation identification system
CN108961019B (en) User account detection method and device
WO2019072098A1 (en) Method and system for identifying core product terms
CN110363206B (en) Clustering of data objects, data processing and data identification method
CN112363923A (en) Test method, device, computer equipment and medium based on questionnaire system
CN104867018A (en) Electronic commerce evaluation judgment system based on evaluation content and ID similarity identification
US10089665B2 (en) Systems and methods for evaluating a credibility of a website in a remote financial transaction
CN108959289B (en) Website category acquisition method and device
CN113779276A (en) Method and device for detecting comments
CN108492112A (en) The method, apparatus and electronic equipment of the false resource transfers of judgement and wash sale
CN104867033A (en) Electronic commerce client evaluation judging and marking system

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20150826