CN105302859B - A kind of intelligent interactive system Internet-based - Google Patents
A kind of intelligent interactive system Internet-based Download PDFInfo
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- CN105302859B CN105302859B CN201510603622.8A CN201510603622A CN105302859B CN 105302859 B CN105302859 B CN 105302859B CN 201510603622 A CN201510603622 A CN 201510603622A CN 105302859 B CN105302859 B CN 105302859B
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
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Abstract
A kind of intelligent interactive system Internet-based, the system are handled user information using following steps:A, the information issued to user segments;B, whether word, word and phrase after segmenting described in step A, which belong to entity, identifies;C, word, word and phrase after segmenting described in step A carry out semantic tagger analysis;D, word, word and phrase after segmenting described in step A carry out text error correction;E, syntactic analysis is carried out to the information that user issues;F, word, word and phrase after segmenting described in the information and step A of user's sending carry out weight correction;G, context processing is carried out to the information that user issues;H, according to the step B-G's as a result, to user issue information carry out similarity calculation, obtain threshold value;I, knowledge base is preset according to threshold value result queries, returns result to user.
Description
Technical field
The present invention relates to a kind of intelligent interactive method, more particularly to a kind of intelligent answer side Internet-based
Method.
Background technique
In traditional intelligent interaction, the general of intelligent interaction copes with complicated dialogue, accuracy using template way
It is lower, or analyzed after carrying out various participles to information, but general word segmentation result type is more, accuracy is lower.
Summary of the invention
The invention discloses a kind of intelligent interactive systems Internet-based, include the following steps:
A, the information issued to user segments;
B, whether word, word and phrase after segmenting described in step A, which belong to entity, identifies;
C, word, word and phrase after segmenting described in step A carry out semantic tagger analysis;
D, word, word and phrase after segmenting described in step A carry out text error correction;
E, syntactic analysis is carried out to the information that user issues;
F, word, word and phrase after segmenting described in the information and step A of user's sending carry out weight correction;
G, context processing is carried out to the information that user issues;
H, according to the step B-G's as a result, to user issue information carry out similarity calculation, obtain threshold value;
I, knowledge base is preset according to threshold value result queries, returns result to user.
Semantic tagger analysis in the step C includes field, different degree, similar word, synonym, cyberspeak.
Text error correction in the step D includes that the service class word and phrase in field carry out phonetic error correction;
Syntactic analysis in the step F is using rule and mask method.
Detailed description of the invention
Fig. 1-ontology and the example of instantiation, succession
Fig. 2-part of speech management
Fig. 3-synonym, weight correction
Specific embodiment
The invention discloses a kind of intelligent interactive systems Internet-based, include the following steps:
A, the information issued to user segments;
Participle is the common technology means of Computational Linguistics or artificial intelligence field, general using " maximum matching participle
Method " or " most probable number method participle ",
B, whether word, word and phrase after segmenting described in step A, which belong to entity, identifies;
It is the instantiation of ontology for entity,
So-called ontology is clear to one kind of concept and is described in detail, is a kind of description method to real world.Or
Person says that ontology is actually the Formal Representation to certain set concept and its mutual relationship among specific area.General packet
Contain:
--- specific instances of ontology (object Object)
--- the attribute of ontology
--- affiliated Ontological classifications.
After instances of ontology, so that it may the attribute of ontology is inherited, for semantic tagger ready for analysis thereafter;
Specifically, such as attached drawing 1, there are many basic businesses for banking, all basic businesses are exactly a kind of
Body for a certain specific ontology, for example handles rule, and marketing activity is exactly the succession of a kind of pair of basic business, is owned
Attribute can inherit.
C, word, word and phrase after segmenting described in step A carry out semantic tagger analysis;
Semantic tagger is analyzed, including two parts of part-of-speech tagging and word sense tagging:
For part-of-speech tagging:The magnetic mark side of the general mistake driving using Hidden Markov Model or based on conversion
Method;
For word sense tagging:Generally use word sense disambiguation method based on mutual information or row's discrimination method based on dictionary;
For the step, when user inputs a problem in robot front end, this problem can carry out word segmentation processing first,
Then it is matched according to the result of participle, therefore the construction superiority and inferiority of part of speech, it is closely coupled with the degree of intelligence of robot.To word
The additions and deletions of class and modification all can be【Part of speech management】Middle realization.
Such as Fig. 2,【Part of speech management】There is " public part of speech " under label, " proprietary part of speech ", wherein being ontology under " public part of speech "
The corresponding part of speech of generic attribute is the customized peculiar part of speech of project under " proprietary part of speech ".
D, word, word and phrase after segmenting described in step A carry out text error correction;
E, syntactic analysis is carried out to the information that user issues;
F, word, word and phrase after segmenting described in the information and step A of user's sending carry out weight correction;
Such as Fig. 3, selection needs the classification right click being linked into, selects in a menu【Newly-built subclassification】, filled out in pop-up box
Enter typonym and saves completion.
In this system, " * " " # " marked beside item name is respectively intended to distinguish the different degree and similarity of part of speech, " * "
Represent important, weight is higher;" # " represents dissmilarity, and similarity is very low;"@" represents the word under the classification with phonetic error correction function
Energy.Subclassification inherits " * " " # " "@" setting of parent classification automatically.
This system can also adjust weight according to user data log.Such as:" no " it is inessential to be based on statistics for word, but passes through
Statistical analysis is crossed, " no " word occurs and sentence tail ratio is higher, and meaning is entirely different, so when " no " word appears in tail,
Such as " I can open CRBT not " adjustment " no " word weight.
G, context processing is carried out to the information that user issues;
H, according to the step B-G's as a result, to user issue information carry out similarity calculation, obtain threshold value;
In addition, this system can also realize " hybrid operation of semantic formula and common question sentence ",
Such as:One standard ask for:" cosmetics mark exaggerates effect, false expression, how to investigate and prosecute?"
The semantic formula that the corresponding standard is asked can be analyzed to:[cosmetics | makeup brand] [falseness] [mark] [punishment]
[method?]
The a certain extension that the corresponding standard is asked ask for:" the false information of cosmetics mark mark, it is industrial and commercial for this behavior
Office takes any method to punish "
Assuming that including above-mentioned knowledge in knowledge base, system can be mixed processing to the information that user provides.Judge
The problem of user, is such as close to standard and asks and can directly answer;It is such as decomposed into semantic formula, then is answered according to semantic formula;
Cannot such as semantic formula be resolved into and be close to extension and ask, then ask answer according to extension;And non-individual is using above-mentioned any one
Mode, to obtain max-thresholds.The answer of i.e. most identical user demand.
I, knowledge base is preset according to threshold value result queries, returns result to user.
Semantic tagger analysis in the step C includes field, different degree, similar word, synonym, cyberspeak.
Specifically, after by carrying out semantic tagger analysis according to above-mentioned aspect, the semanteme of the word divided is accurate, ambiguity
It substantially eliminates.
Text error correction in the step D includes that the service class word and phrase in field carry out phonetic error correction;
Syntactic analysis in the step E is using rule and mask method.
Claims (4)
1. a kind of intelligent interactive system Internet-based, the system is handled user information using following steps:
A, the information issued to user segments;
B, whether word, word and phrase after segmenting described in step A, which belong to entity, identifies;
C, word, word and phrase after segmenting described in step A carry out semantic tagger analysis;
D, word, word and phrase after segmenting described in step A carry out text error correction;
E, syntactic analysis is carried out to the information that user issues;
F, according to user data log, word, word and phrase after segmenting described in the information and step A of user's sending carry out weight
Correction;
G, context processing is carried out to the information that user issues;
H, according to the step B-G's as a result, to user issue information carry out similarity calculation, obtain threshold value;In the phase
Mixed processing is carried out to the information that user issues like in degree calculating, including:The problem of judging user is such as close to that standard asks can be straight
It takes back and answers;It is such as decomposed into semantic formula, then is answered according to semantic formula;Semantic formula cannot such as be resolved into and close to
It is asked in extension, then asks answer according to extension;
I, knowledge base is preset according to threshold value result queries, returns result to user.
2. a kind of intelligent interactive system Internet-based according to claim 1, it is characterised in that:
Semantic tagger analysis in the step C includes field, different degree, similar word, synonym, cyberspeak.
3. a kind of intelligent interactive system Internet-based according to claim 1, it is characterised in that:
Text error correction in the step D includes that the service class word and phrase in field carry out phonetic error correction.
4. a kind of intelligent interactive system Internet-based according to claim 1, it is characterised in that:
Syntactic analysis in the step E is using rule and mask method.
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CN106485328B (en) * | 2016-10-31 | 2020-06-19 | 上海智臻智能网络科技股份有限公司 | Information processing system and method |
CN108073587B (en) * | 2016-11-09 | 2022-05-27 | 阿里巴巴集团控股有限公司 | Automatic question answering method and device and electronic equipment |
CN106599163B (en) * | 2016-12-08 | 2019-11-22 | 上海云信留客信息科技有限公司 | A kind of data digging method and device for big data |
CN110175230A (en) * | 2019-05-29 | 2019-08-27 | 广州伟宏智能科技有限公司 | Intelligent robot interactive system |
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CN101174259A (en) * | 2007-09-17 | 2008-05-07 | 张琰亮 | Intelligent interactive request-answering system |
CN101373532A (en) * | 2008-07-10 | 2009-02-25 | 昆明理工大学 | FAQ Chinese request-answering system implementing method in tourism field |
CN101510221A (en) * | 2009-02-17 | 2009-08-19 | 北京大学 | Enquiry statement analytical method and system for information retrieval |
CN104657346A (en) * | 2015-01-15 | 2015-05-27 | 深圳市前海安测信息技术有限公司 | Question matching system and question matching system in intelligent interaction system |
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US10515154B2 (en) * | 2014-03-12 | 2019-12-24 | Sap Se | Systems and methods for natural language processing using machine-oriented inference rules |
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CN101174259A (en) * | 2007-09-17 | 2008-05-07 | 张琰亮 | Intelligent interactive request-answering system |
CN101373532A (en) * | 2008-07-10 | 2009-02-25 | 昆明理工大学 | FAQ Chinese request-answering system implementing method in tourism field |
CN101510221A (en) * | 2009-02-17 | 2009-08-19 | 北京大学 | Enquiry statement analytical method and system for information retrieval |
CN104657346A (en) * | 2015-01-15 | 2015-05-27 | 深圳市前海安测信息技术有限公司 | Question matching system and question matching system in intelligent interaction system |
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