Method for searching session on basis of partially observable Markov decision process models

A Markov decision-making and process model technology, which is applied in the field of information retrieval based on session search, and can solve the problems of difficulty in acquiring users accurately and changing patterns without uniform rules.

Inactive Publication Date: 2018-02-23
NANJING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In conversational search, there is no uniform pattern of user query change patterns, and it is difficult for search engines to accurately obtain user intentions, so conversational search is a challenging information retrieval task.
Existing learning methods are difficult to exploit query changes or apply directly to conversational search

Method used

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  • Method for searching session on basis of partially observable Markov decision process models
  • Method for searching session on basis of partially observable Markov decision process models
  • Method for searching session on basis of partially observable Markov decision process models

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Embodiment Construction

[0131] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0132] Such as figure 1 As shown, the conversational search system based on the partially observable Markov decision process model first obtains the corpus and conversational behavior data, and generates them as training files. After data preprocessing, calculation of statistics and state transition probability, the training file is parsed and P us (t|d), to update the state transition function P(s|ω) and the observation function O(s, a, ω). Retrieval can be performed after the training is completed, and the document correlation degree is calculated according to the query statement, so as to obtain the recommendation result.

[0133] Such as figure 2 As shown, in the data preparation stage of the present invention, the corpus is marked in units of topics, and the interaction process of users when retrieving topics is recorded. After recording all retrieval inter...

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Abstract

The invention discloses a method for searching session on the basis of partially observable Markov decision process models. The method includes steps of 1), carrying out preparation phases, to be morespecific, marking corpora on the basis of themes used as units, recording interaction processes when the themes are retrieved by users and generating training files after all retrieval interaction isrecorded; 2), carrying out training phases, to be more specific, initializing statistics, computing initial state transition functions, parsing interactive data of the session from the training filesand updating the state transition functions according to the interactive data; 3), carrying out retrieval phases, to be more specific, receiving initial query statements, and updating the query statements when the users dissatisfy with fed documents until satisfactory document results are fed to the users.

Description

technical field [0001] The invention relates to information retrieval based on session search, in particular to a session search method based on hidden Markov decision process model. Background technique [0002] Conversational search refers to the technology of information retrieval through the interaction between search engine and users. The search engine infers which information the user is interested in based on the constantly changing query content and operations of the user during the search process, and continuously optimizes the search results until the user is satisfied with the search results. In conversational search, there is no uniform pattern of user query change patterns, and it is difficult for search engines to accurately obtain user intentions, so conversational search is a challenging information retrieval task. Existing learning methods are difficult to exploit query changes or apply directly to conversational search. [0003] Hidden Markov decision pro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/951G06F16/3329G06F16/3349
Inventor 刘峰沈佳楠伍佳艺花霞
Owner NANJING UNIV
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