An Information Retrieval Model for the Semantic Web

被引：2
|
作者：
Silva, Fabio [1 ]
Girardi, Rosario [1 ]
Drumond, Lucas [1 ]
机构：
[1] UFMA Fed Univ Maranhao, Sao Luis, Brazil
来源：
PROCEEDINGS OF THE 2009 SIXTH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: NEW GENERATIONS, VOLS 1-3 | 2009年
关键词：
Information retrieval model; Semantic Web; Semantic case; Matching; Similarity;
D O I：
10.1109/ITNG.2009.116
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Exploring the metadata associated with documents in the Semantic Web is a way to increase the precision of information retrieval systems. Systems have been established so far failed to overcome fully the limitations of search based on keywords. Such systems are built from variations of classic models that represent information by keywords and work upon statistical correlations. This work proposes an information retrieval model to find information items with similar semantic content that a given user's query. The information items internal representation is based on user interest groups, called "semantic cases". The model also defines a similarity measure for ordering the results based on semantic distance between semantic cases items.
引用
收藏
页码：143 / 148
页数：6
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