A survey on socio-semantic information retrieval

被引:9
作者
Schoefegger, Karin [1 ]
Tammet, Tanel [2 ]
Granitzer, Michael [3 ]
机构
[1] Graz Univ Technol, Knowledge Management Inst, Graz, Austria
[2] ELIKO Technol Competence Ctr, Tallinn, Estonia
[3] Univ Passau, Media Comp Sci, Passau, Germany
关键词
Information retrieval; Personalized search; Emergent semantics; Formal semantics; Content semantics;
D O I
10.1016/j.cosrev.2013.03.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The rise of the Social Web and advances in the Semantic Web provides unprecedented possibilities for the development of novel methods to enhance the information retrieval (IR) process by including varying degrees of semantics. We shed light on the corresponding notion of semantically-enhanced information retrieval by presenting state-of-the art techniques in related research areas. We describe techniques based on the main processes of a typical IR workflow and map them onto three main types of semantics, which vary from formal semantic knowledge representations and content-based semantics to social semantics emerging through usage and user interactions. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:25 / 46
页数:22
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