A Method for User Profile Learning in Document Retrieval System Using Bayesian Network

被引：2

作者：

Maleszka, Bernadetta ^{[1
]}

机构：

[1] Wroclaw Univ Sci & Technol, Fac Comp Sci & Management, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland

来源：

INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2017, PT I | 2017年 / 10191卷

关键词：

Document retrieval; Knowledge integration; User profile adaptation; Ontology-based user profile; Bayesian network; FRAMEWORK;

D O I：

10.1007/978-3-319-54472-4_26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

User modeling methods are developed by many researches in area of document retrieval systems. The main reason is that the system can not present the same results for every user. Each user can have different information needs even if he uses the same terms to formulate his query. In this paper we present the solution for the problem. We propose a method for user profile building and updating using Bayesian network approaches which allows to discover dependencies between terms. Additionally, we use domain ontology of terms to simplify the calculations. Performed experiments have shown that the quality of presented methods is promising.

引用

页码：269 / 277

页数：9

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