Towards a Unified Supervised Approach for Ranking Triples of Type-Like Relations

Knowledge bases play a crucial role in modern search engines and provide users with information about entities. A knowledge base may contain many facts (i.e., RDF triples) about an entity, but only a handful of them are of significance for a searcher. Identifying and ranking these RDF triples is ess...

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Bibliographic Details
Published inAdvances in Information Retrieval pp. 707 - 714
Main Authors Shahshahani, Mahsa S., Hasibi, Faegheh, Zamani, Hamed, Shakery, Azadeh
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Entity facts
Knowledge bases
Triple scoring
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Summary:Knowledge bases play a crucial role in modern search engines and provide users with information about entities. A knowledge base may contain many facts (i.e., RDF triples) about an entity, but only a handful of them are of significance for a searcher. Identifying and ranking these RDF triples is essential for various applications of search engines, such as entity ranking and summarization. In this paper, we present the first effort towards a unified supervised approach to rank triples from various type-like relations in knowledge bases. We evaluate our approach using the recently released test collections from the WSDM Cup 2017 and demonstrate the effectiveness of the proposed approach despite the fact that no relation-specific feature is used.
ISBN:9783319769400
3319769405
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-76941-7_66