CN103279528A - Question-answering system and question-answering method based on man-machine integration - Google Patents
Question-answering system and question-answering method based on man-machine integration Download PDFInfo
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Abstract
The invention provides a question-answering system based on man-machine integration. The question-answering system based on man-machine integration comprises an input module, a denoising module, a semantic parsing module, an information processing module, an intelligent decision-making module, an output module, a manual customer service processing module and a training module. The invention further provides a question-answering method based on man-machine integration. The method comprises the steps of inputting questioning information; converting the questioning information into standard text formatting information; carrying out denoising and module structuralization on the text formatting information; carrying out semantic parsing on the questioning information; judging an information processing result and making a decision; generating an answer and inputting the answer if the answer is correct; presenting the question to manual customer service to be processed if no answer is available or the answer is wrong, judging again according to a processing result and making a decision, training judging capacity and decision making capacity, and outputting a correct answer. According to the question-answering system and the question-answering method based on man-machine integration, self-learning capacity and self-improving capacity are improved, humanization and intelligentization are improved, and the accuracy and the timeliness of the system are guaranteed.
Description
Technical field
The present invention relates to information retrieval and inquiry field, relate in particular to a kind of question answering system based on man-machine combination and method.
Background technology
Question answering system is a kind of advanced form of information retrieval system.It can answer the problem that the user proposes with natural language with accurate, succinct natural language.The main cause that its research is risen is that people are to obtaining the demand of information quickly and accurately.Question answering system is research direction that receives much attention and have the broad development prospect in present artificial intelligence and the natural language processing field.
Existing question answering system mainly is to realize by the algorithm logic of computing machine, and basic process comprises case study, information retrieval and three processes of answer extraction.In these three processes, careless mistake appears in any one link, and the user can't obtain correct result.What is more important, because the adjustability of this question answering system is relatively poor, can't utilize customer problem, allow and oneself become more intelligent, so carry when the user imports same asking again, based on same logic, the user still can't obtain correct result, unless the algorithm logic of this cover question and answer system is made amendment.
This shows that the adjustability of question answering system has become the key issue that influences question answering system accuracy and promptness.Before this, domestic certain chat robots provides a kind of function of instruction, and the user can look after and guide it after registering login, but this instruction is machinery data is filled in the question answering system by force, and is as index with certain keyword.Like this, no matter ask what problem, as long as relate to these keywords, will return the content of respective user instruction, so a lot of irrelevant answers occurred.Though this question answering system has possessed adjustability, do not improve self-teaching and the self promotion ability of question answering system, intellectuality has not just more been known where to begin; Simultaneously, this instruction function is finished by program module, lacks manually to participate in, and hommization is not strong.
Summary of the invention
The objective of the invention is at the deficiencies in the prior art, a kind of question answering system based on man-machine combination and method are provided, introduce artifact, adopt artificial instruction mode, improve self-teaching and the self promotion ability of question answering system, increase hommization and intellectuality simultaneously, guarantee accuracy and the promptness of system.
For achieving the above object, the invention provides a kind of question answering system based on man-machine combination and method, comprising:
Load module is used for input user speech, text and operational order and puts question to information, gathers customer parameter information, and puts question to information and customer parameter information all to be converted to the normative text format information user;
The denoising module is used for text formatting information, carries out denoising and modular structure processing;
Semantic meaning analysis module is used for that user's information of puing question to of denoising and modularization processing is carried out semanteme and resolves;
Message processing module is used for resolving information is handled, and generates result;
The intelligent decision module is for the information processing result being judged and determining;
Output module is used for puing question to answer according to judgement and determination result output user;
Artificial customer service processing module is used for receiving the nothing of exporting and answers and the false answer result, and the pedestrian worker that goes forward side by side handles;
Training module is for receiving artificial result and this intelligent decision module being trained.
Further, this load module comprises:
Voice input module is used for the input of user speech information;
The text load module is used for the input of user version information;
The operation load module is used for the input of user's operational order;
The parameter acquisition module is used for gathering user's various parameter informations;
Text conversion module, being used for puing question to information and customer parameter information translation with the user is text formatting information.
Further, this semantic meaning analysis module comprises:
Word-dividing mode is used for setting up a cover based on the statement of Modern Chinese, the participle algorithm model of sentence structure, utilizes a large amount of basicvocabulary data, adopts smallest particles to divide word algorithm that participle is carried out in natural language and the instruction of user's input;
The weight allocation module is used for to user's linguistic context, context, preference and parameters, carrying out first combination and the weight allocation of key word and intention after the participle, parses key word;
The structured combinations module is used for the key word that parses is carried out structured combinations, obtains analysis result.
Further, this message processing module comprises:
Authentication module is used for judging whether the domain information of this semantic meaning analysis module is comprehensive, if not comprehensive, sets up this context model, preserves this session log, changes corresponding processing platform over to; If directly change corresponding processing platform over to comprehensively;
Processing platform is used for the domain information of checking is handled, and generates the baseline results data.
A kind of answering method based on man-machine combination may further comprise the steps:
Step 1, input user speech, text and operational order are putd question to information, gather customer parameter information;
Step 2, puing question to information and customer parameter information translation with the user is the normative text format information;
Step 3 to text formatting information, is carried out denoising and modular structure processing;
Step 4 is carried out semanteme to user's information of puing question to of denoising and modularization processing and is resolved;
Step 5 is judged and is determined the information processing result;
Step 6 generates the user and puts question to answer, if answer is correct, and directly output; If answer does not have answer or answer is incorrect, submit to artificial customer service to handle problem, judge again and determines according to result, and to judging and deciding ability is trained, export correct option.
Further, this step 4 comprises following substep:
1, adopt the branch word algorithm that participle is carried out in natural language and the instruction of user's input;
2, to user's linguistic context, context, preference and parameters, carry out first combination and the weight allocation of key word and intention, parse key word;
3, the key word that parses is carried out structured combinations, obtain analysis result.
Compared with prior art, the invention has the beneficial effects as follows: by introducing artifact, adopt artificial instruction mode, improved self-teaching and the self promotion ability of question answering system, increase hommization and intellectuality simultaneously, guaranteed accuracy and the promptness of system.
Description of drawings
Fig. 1 is the system construction drawing of a kind of question answering system and method based on man-machine combination of the present invention;
Fig. 2 is the method flow diagram of a kind of question answering system and method based on man-machine combination of the present invention.
Fig. 3 is the load module structural drawing;
Fig. 4 is the semantic meaning analysis module structural drawing;
Fig. 5 is the message processing module structural drawing.
Embodiment
The present invention is described in detail below in conjunction with each embodiment shown in the drawings; but should be noted that; these embodiments are not limitation of the present invention; the function that those of ordinary skills do according to these embodiments, method or structural equivalent transformation or alternative all belong within protection scope of the present invention.
Join shown in Figure 1ly, Fig. 1 is system construction drawing of the present invention.
In the present embodiment, a kind of question answering system based on man-machine combination comprises:
Denoising module 20 is used for text formatting information, carries out denoising and modular structure processing;
Semantic meaning analysis module 30 is used for that user's information of puing question to of denoising and modularization processing is carried out semanteme and resolves;
Intelligent decision module 50 is for the information processing result being judged and determining;
This intelligent decision module 50 is one can be learnt, and can sum up the system of conclusion, and it can use to learn and conclude summary by the experiment of given data.In the human perception field of artificial intelligence, we are by can the conduct oneself decision problem of worker's perception aspect of the application of mathematical statistics, and namely by statistical method, this module can similar people equally have simple deciding ability and simple judgement.
Output module 60 is used for puing question to answer according to judgement and determination result output user;
Artificial customer service processing module 70 is used for receiving the nothing of exporting and answers and the false answer result, and the pedestrian worker that goes forward side by side handles;
Training module 80 is for receiving artificial result and this intelligent decision module 50 being trained.
Such as user's input " to five road junctions how by bus Xizhimen ", existing hypothesis can't be made correct answer, and this problem will be pushed to this artificial customer service processing module 70.This artificial customer service processing module 70 is handled this problem, and beams back this training module 80 with specific rule.80 pairs of these intelligent decision modules 50 of this training module are trained, and this intelligent decision module 50 begins this problem is carried out modeling by the correction of training sample, just have afterwards to solve to follow these question marks seemingly or the ability of relevant a series of problems.
Ginseng Fig. 3, Fig. 4 and shown in Figure 5, Fig. 3 is the load module structural drawing; Fig. 4 is the semantic meaning analysis module structural drawing; Fig. 5 is the message processing module structural drawing.
This load module 10 comprises:
This semantic meaning analysis module 30 comprises:
Word-dividing mode 301 is used for setting up a cover based on the statement of Modern Chinese, the participle algorithm model of sentence structure, utilizes a large amount of basicvocabulary data, adopts smallest particles to divide word algorithm that participle is carried out in natural language and the instruction of user's input.
This message processing module 40 comprises:
" domain information " is the function classification of question answering system definition, and each big function classification all belongs to an independent domain, and a complete domain comprises all information of corresponding function.Need following essential information as: flight domain: the date, (form was: yyyy-MM-dd), set out city or airport, purpose city or airport; In addition, some optional informations, as the classification of attending a banquet in addition, information of discount, airline's information, time interval section (00:00-24:00) etc.
" domain information " checking mainly is the checking of this domain being carried out essential information, see whether essential information all possesses on request, if all possess on request, then verifying that the domain information of passing through directly changes corresponding processing platform over to and carries out the data processing.If do not possess, then check which information of falling vacant, to add Context identifier and corresponding informance field item is added sign according to the domain information of the item of information that lacks, unification is given and is handled and output module.
Join shown in Figure 2ly, Fig. 2 is method flow diagram of the present invention.
In the present embodiment, a kind of answering method based on man-machine combination may further comprise the steps:
Step 1, input user speech, text and operational order are putd question to information, gather customer parameter information;
Step 2, puing question to information and customer parameter information translation with the user is the normative text format information;
Step 3 to text formatting information, is carried out denoising and modular structure processing.
Step 4 is carried out semanteme to user's information of puing question to of denoising and modularization processing and is resolved;
Step 5 is judged and is determined the information processing result;
Step 6 generates the user and puts question to answer, if answer is correct, and directly output; If answer does not have answer or answer is incorrect, submit to artificial customer service to handle problem, judge again and determines according to result, and to judging and deciding ability is trained, export correct option.
Above-mentioned steps 4 comprises following substep:
1, adopt the branch word algorithm that participle is carried out in natural language and the instruction of user's input;
2, to user's linguistic context, context, preference and parameters, carry out first combination and the weight allocation of key word and intention, parse key word;
3, the key word that parses is carried out structured combinations, obtain analysis result.
The invention provides a kind of question answering system based on man-machine combination and method, it is by introducing artifact, adopt artificial instruction mode, self-teaching and the self promotion ability of question answering system have been improved, hommization and intellectuality have been increased, guaranteed accuracy and the promptness of system, made question answering process have more interest and practicality simultaneously, compared pure manual system and saved a large amount of manpower and materials costs.
To those skilled in the art, obviously the invention is not restricted to the details of above-mentioned one exemplary embodiment, and under the situation that does not deviate from spirit of the present invention or essential characteristic, can realize the present invention with other concrete form.Therefore, no matter from which point, all should regard embodiment as exemplary, and be nonrestrictive, scope of the present invention is limited by claims rather than above-mentioned explanation, therefore is intended to include in the present invention dropping on the implication that is equal to important document of claim and all changes in the scope.Any Reference numeral in the claim should be considered as limit related claim.
In addition, be to be understood that, though this instructions is described according to embodiment, but be not that each embodiment only comprises an independently technical scheme, this narrating mode of instructions only is for clarity sake, those skilled in the art should make instructions as a whole, and the technical scheme among each embodiment also can form other embodiments that it will be appreciated by those skilled in the art that through appropriate combination.
Claims (6)
1. the question answering system based on man-machine combination is characterized in that, comprising:
Load module is used for input user speech, text and operational order and puts question to information, gathers customer parameter information, and puts question to information and customer parameter information all to be converted to the normative text format information user;
The denoising module is used for text formatting information, carries out denoising and modular structure processing;
Semantic meaning analysis module is used for that user's information of puing question to of denoising and modularization processing is carried out semanteme and resolves;
Message processing module is used for resolving information is handled, and generates result;
The intelligent decision module is for the information processing result being judged and determining;
Output module is used for puing question to answer according to judgement and determination result output user;
Artificial customer service processing module is used for receiving the nothing of exporting and answers and the false answer result, and the pedestrian worker that goes forward side by side handles;
Training module is for receiving artificial result and described intelligent decision module being trained.
2. a kind of question answering system based on man-machine combination according to claim 1 is characterized in that described load module comprises:
Voice input module is used for the input of user speech information;
The text load module is used for the input of user version information;
The operation load module is used for the input of user's operational order;
The parameter acquisition module is used for gathering user's various parameter informations;
Text conversion module, being used for puing question to information and customer parameter information translation with the user is text formatting information.
3. a kind of question answering system based on man-machine combination according to claim 1 is characterized in that described semantic meaning analysis module comprises:
Word-dividing mode is used for setting up a cover based on the statement of Modern Chinese, the participle algorithm model of sentence structure, utilizes a large amount of basicvocabulary data, adopts smallest particles to divide word algorithm that participle is carried out in natural language and the instruction of user's input;
The weight allocation module is used for to user's linguistic context, context, preference and parameters, carrying out first combination and the weight allocation of key word and intention after the participle, parses key word;
The structured combinations module is used for the key word that parses is carried out structured combinations, obtains analysis result.
4. a kind of question answering system based on man-machine combination according to claim 1 is characterized in that described message processing module comprises:
Authentication module is used for judging whether the domain information of this semantic meaning analysis module is comprehensive, if not comprehensive, sets up this context model, preserves this session log, changes corresponding processing platform over to; If directly change corresponding processing platform over to comprehensively;
Processing platform is used for the domain information of checking is handled, and generates the baseline results data.
5. the answering method based on man-machine combination is characterized in that, may further comprise the steps:
Step 1, input user speech, text and operational order are putd question to information, gather customer parameter information;
Step 2, puing question to information and customer parameter information translation with the user is the normative text format information;
Step 3 to text formatting information, is carried out denoising and modular structure processing;
Step 4 is carried out semanteme to user's information of puing question to of denoising and modularization processing and is resolved;
Step 5 is judged and is determined the information processing result;
Step 6 generates the user and puts question to answer, if answer is correct, and directly output; If answer does not have answer or answer is incorrect, submit to artificial customer service to handle problem, judge again and determines according to result, and to judging and deciding ability is trained, export correct option.
6. a kind of intelligent question and answer exchange method based on portable terminal according to claim 5 is characterized in that described step 4 comprises following substep:
(1) adopt the branch word algorithm that participle is carried out in natural language and the instruction of user's input;
(2) to user's linguistic context, context, preference and parameters, carry out first combination and the weight allocation of key word and intention, parse key word;
(3) key word that parses is carried out structured combinations, obtain analysis result.
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