Intelligent question and answer method, knowledge base optimizing method and device and intelligent knowledge base

A knowledge base and knowledge point technology, applied in the computer field, can solve the problems of not being able to contain verbs, occupying storage resources, unable to provide correct answers, etc., so as to improve the matching success rate, optimize the structure, and improve the accuracy.

Active Publication Date: 2016-08-24
SHANGHAI XIAOI ROBOT TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, if you use the above enumeration method to write extended questions, the following problems will occur: 1. The enumerated questions occupy a lot of storage resources; 2.

Method used

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  • Intelligent question and answer method, knowledge base optimizing method and device and intelligent knowledge base
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  • Intelligent question and answer method, knowledge base optimizing method and device and intelligent knowledge base

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Embodiment 1

[0026] According to an embodiment of the present invention, an intelligent question answering method is provided, figure 1 It is a flow chart of the intelligent question answering method of the embodiment of the present invention, such as figure 1 As shown, the intelligent question answering method according to the embodiment of the present invention includes the following processing:

[0027] Step 101, providing a knowledge base, the knowledge base includes multiple knowledge points, each knowledge point includes an answer and one or more questions, at least some of the questions use semantic expressions, and the semantic expressions include parts of speech; wherein, the knowledge base also includes Fuzzy knowledge points.

[0028] In step 101, the most primitive and simplest form of the knowledge points in the knowledge base is the commonly used FAQ, and the general form is a "question-answer" pair, wherein the "ask" is a standard question, and the "answer" is Answer. For...

Embodiment 2

[0068] According to an embodiment of the present invention, a knowledge base optimization method is provided, figure 2 is a flowchart of a knowledge base optimization method in an embodiment of the present invention, such as figure 2 As shown, the knowledge base optimization method according to the embodiment of the present invention includes the following processing:

[0069] Step 201, performing priority marking on fuzzy knowledge points and / or non-fuzzy knowledge points, wherein the priority marking is used to identify the order of semantic similarity calculation;

[0070] It should be noted that, in the embodiment of the present invention, the above-mentioned fuzzy knowledge points and non-fuzzy knowledge points are set in a knowledge base, and the knowledge base includes a plurality of fuzzy knowledge points and non-fuzzy knowledge points, and each knowledge point includes an answer and one or A plurality of questions, at least some number of the questions, employ sema...

Embodiment 3

[0117]According to an embodiment of the present invention, a knowledge base optimization device is provided, Figure 4 is a schematic diagram of the knowledge base optimization device of the device embodiment of the present invention, such as Figure 4 As shown, the knowledge base optimization device according to the embodiment of the present invention includes: a priority labeling module 40, and a correction weight labeling module 42. The above-mentioned modules in the embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0118] A priority marking module 40, configured to perform priority marking on fuzzy knowledge points and / or non-fuzzy knowledge points, wherein the priority marking is used to identify the order in which the semantic similarity is calculated;

[0119] Specifically, fuzzy knowledge points and / or non-fuzzy knowledge points are set in the knowledge base, the knowledge base includes multiple knowled...

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Abstract

The invention discloses an intelligent question and answer method and device, a knowledge base optimizing method and device and an intelligent knowledge base. The intelligent question and answer method comprises the steps that a knowledge base is provided, wherein the knowledge base comprises a plurality of knowledge points, each knowledge point comprises an answer and one or more questions, semantic expressions are adopted for at least part of the questions, and the semantic expressions comprise parts of speeches; input information of a user is obtained; semantic similarity calculation is carried out on the input information and the questions in the knowledge points, and when the maximum semantic similarity value obtained through calculation is larger than a preset threshold value, the answer in the knowledge point corresponding to the maximum semantic similarity value is sent to the user, wherein the knowledge base comprises fuzzy knowledge points, in the calculation process of semantic similarity, the semantic similarity of the fuzzy knowledge points and the input information is calculated only when the maximum semantic similarity value of the knowledge points except the fuzzy knowledge points and the input information is smaller than the preset threshold value, and answers in the fuzzy knowledge points are sent to the user when the semantic similarity of the fuzzy knowledge points and the input information is larger than the preset threshold value.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an intelligent question answering method and device, a knowledge base optimization method and device, and an intelligent knowledge base. Background technique [0002] In the question answering system, the knowledge base plays a crucial role. The knowledge base includes multiple knowledge points, and each knowledge point includes an answer, a standard question and / or multiple extended questions corresponding to the standard question. Standard questions and extended questions can be in the form of ordinary questions or semantic expressions, which are distinguished according to whether they include parts of speech. Semantic expressions include parts of speech. Parts of speech are divided according to the semantics of words. A group of related words are organized together to form a tree-structured part-of-speech library. Any non-leaf node in this tree-like structure is is called a...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/3344
Inventor 曾永梅李波朱频频
Owner SHANGHAI XIAOI ROBOT TECH CO LTD
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