A Method of Personalized Web Search Result Clustering Based on Formal Concept Analysis

DOI

10.2991/iske.2007.283How to use a DOI?

Keywords

Web search result clustering; personalized document clustering; Formal Concept Analysis (FCA); search engine

Abstract

Most existing Web search result clustering techniques, generally anchoring in pure content-based analysis, generate a single set of clusters for all individuals without tailoring to individuals’ preferences and thus are unable to support personalization. In this paper, we incorporate a target user’s categorization preferences into the Web search result clustering process using Formal Concept Analysis (FCA). Personalized conceptual clusters hierarchy of Web search result will be built combining content analysis and user information analysis. We focus on the target user’s categorization preference extracting and cluster hierarchy building based on FCA.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Wang
AU  - Yajun Du
PY  - 2007/10
DA  - 2007/10
TI  - A Method of Personalized Web Search Result Clustering Based on Formal Concept Analysis
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1651
EP  - 1656
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.283
DO  - 10.2991/iske.2007.283
ID  - Wang2007/10
ER  -