Question sentence recommendation method and system

A recommendation method and recommendation system technology, applied in the field of question recommendation methods and systems, can solve problems such as lowering the retrieval accuracy rate, difficulty in correctly selecting keywords, and difficulty in judging the real intention of users, and achieve the effect of improving the accuracy of answers

Active Publication Date: 2018-02-16
GUANGZHOU DUOYI NETWORK TECH +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] 1. Difficult to choose good keywords correctly
[0010] 2. It is difficult to determine the weight of keywords
[0011] 3. Although the expansion of keywords improves the recall rate of the system, if the expansion is not appropriate, the correct rate

Method used

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  • Question sentence recommendation method and system
  • Question sentence recommendation method and system
  • Question sentence recommendation method and system

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Embodiment 1

[0060] In the following, an example is used to introduce the steps and flow of the question recommendation method of the present invention, specifically as follows:

[0061] Please also see figure 2 , which is a flow chart of the steps of the question recommendation method of the present invention. The present invention provides a kind of question recommendation method, comprises the following steps:

[0062] S1: Receive corpus data, where the corpus data is multi-round question-answer data. The corpus is in the chat logs of different users, and each question of the user in the question and answer is extracted.

[0063] S2: Convert the corpus data to generate positive example pairs, the positive example pairs are question-answer pairs consisting of correct "question-answer", or question pairs consisting of "question-next question" in the correct sequence.

[0064] A counter-example pair is generated by combining random sampling with the corpus data, and the counter-example...

Embodiment 2

[0115] In order to realize the method for recommending questions in Embodiment 1, Embodiment 2 provides a system for recommending questions. details as follows:

[0116] see Figure 4 , which is a module connection block diagram of the question recommendation system of the present invention. The present invention also provides a question recommendation system, which includes a corpus receiving module 1, a positive example pair generation module 2, a negative example pair generation module 3, a sentence vector matrix acquisition module 4, a dot product calculation module 5, and a sentence semantic vector acquisition module 6 and prediction model acquisition module 7.

[0117] The corpus receiving module 1 is used to receive corpus data, and the corpus data is multi-round question-and-answer data;

[0118] The positive example pair generation module 2 is used to convert the corpus data into a positive example pair, the positive example pair is a question-answer pair composed ...

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Abstract

The invention provides a question sentence recommendation method. The method includes the following steps: S1, receiving corpus data, wherein the corpus data are multi-round question and answer data;S2, transforming the corpus data to generate positive example pairs, and generating counter example pairs through random sampling and combination with the corpus data; S3, carrying out word vectorization on the positive example pairs and the counter example pairs through a word2vec model to respectively acquire sentence vector matrices; S4, inputting the sentence vector matrices into a hidden layer, and carrying out dot product operating on the sentence vector matrices and a weight matrix to obtain new sentence vector matrices; S5, inputting the sentence vector matrices into a convolutional neural network, and carrying out convolution and pooling sampling operation to obtain semantic vectors of the sentences; and S6, carrying out non-linear transformation on the semantic vectors of the sentences, calculating cosine similarity of the semantic vectors of the positive example sentence pairs and cosine similarity of the counter example sentence pairs, and finally, acquiring a prediction model. The invention also provides a question sentence recommendation system used for realizing the above-mentioned method.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a question recommendation method and system. Background technique [0002] In the existing question answering system, the user usually asks a question first, and then the system will give an answer. In this way, the system is often passive, looking for answers based on the user's questions. see figure 1 , which is a flowchart of an existing question matching method. Currently, a keyword-based question matching method is usually used for question matching, and the specific steps are as follows: [0003] 1) Perform word segmentation and part-of-speech tagging on the questions submitted by players [0004] 2) Use the stop word list to filter out the stop words in the question [0005] 3) Classify the questions submitted by the players to determine the type of questions [0006] 4) According to the question type, the keywords are appropriately expanded [0007] 5) Divide...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/3322G06F16/3325G06F16/3329G06F16/3331G06F16/3349G06F16/36
Inventor 徐波
Owner GUANGZHOU DUOYI NETWORK TECH
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