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Personalized search algorithm with enhanced time information

A time information and search algorithm technology, applied in the field of artificial intelligence, can solve time-sensitive problems

Pending Publication Date: 2021-01-05
RENMIN UNIVERSITY OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, users' long-term re-query behavior will also reflect time-sensitive characteristics, which was not considered in previous personalized search work

Method used

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  • Personalized search algorithm with enhanced time information
  • Personalized search algorithm with enhanced time information
  • Personalized search algorithm with enhanced time information

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Embodiment Construction

[0061] The following is a preferred embodiment of the present invention and the technical solutions of the present invention are further described in conjunction with the accompanying drawings, but the present invention is not limited to this embodiment.

[0062] The present invention proposes a personalized search algorithm enhanced by time information. First, the personalized search algorithm enhanced by time information is defined:

[0063] Personalized search aims to utilize the user's search history, establish the user's interest representation, and re-rank candidate documents based on the user's interest representation. Suppose there is a set of users U={u 1 , u 2 ... u M}. For each user u, can access his query log where (q i ,D i , t i ) means that user u found query q on the search engine at time t i, so as to obtain the search result D i . D can be further defined i for D i ={d i1 ,... d im}, where d ij Refers to the query q i corresponding to the j...

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PUM

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Abstract

Through a method in the field of artificial intelligence, a personalized search algorithm with enhanced time information is realized, and on the basis of inputting a user set, two time-aware LSTM structures are designed through an original correlation score obtained by a recurrent neural network to obtain a query intention of a user and a document interest representing the short-term interest of the user. A long-term query intention and a long-term document interest of a user are obtained by utilizing query-based Gaussian mixture distribution taking time as an independent variable; and finally, a neural network model is utilized to consider the original correlation score and the personalized score at the same time to carry out final calculation on the personalized score of the document. Through the above means, the user interests are modeled in the continuous time space, so that more accurate user interest representation is constructed, and the personalized sorting effect is improved.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a personalized search algorithm enhanced by time information. Background technique [0002] Personalized search is one of the main goals of major search engines. Now the mainstream personalized algorithm is based on text analysis, that is, to establish a user interest model, and then compare the similarity between user interest and candidate documents to rearrange the results. The main basis for establishing the user model is the user's historical click behavior, so as to describe the user's interest characteristics, so as to complete the personalized document sorting. The main goal of personalized search is to return personalized sorted lists for different users according to their different interests. The basic idea of ​​the prior art is to first use the user history to model user interests, and then consider the relevance of documents and queries as well as the similarit...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/9538G06N3/04G06N3/08
CPCG06F16/9535G06F16/9538G06N3/049G06N3/084G06N3/044Y02D10/00
Inventor 窦志成马正一
Owner RENMIN UNIVERSITY OF CHINA
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