Recommendation of Text Tags in Social Applications Using Linked Data

We present a recommender system that suggests geo-located text tags by using linguistic information extracted from Linked Data sets available on the Web. The recommender system performs tag matching by measuring the semantic similarity of natural language texts. Our approach evaluates similarity usi...

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Bibliographic Details
Published inCurrent Trends in Web Engineering pp. 187 - 191
Main Authors Calì, Andrea, Capuzzi, Stefano, Dimartino, Mirko Michele, Frosini, Riccardo
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Link Data
Link Open Data
Recommender System
Semantic Similarity
Social Application
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Summary:We present a recommender system that suggests geo-located text tags by using linguistic information extracted from Linked Data sets available on the Web. The recommender system performs tag matching by measuring the semantic similarity of natural language texts. Our approach evaluates similarity using a technique that compares sentences taking into account their grammatical structure.
ISBN:3319042432
9783319042435
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-04244-2_17