research-article

FarsBase: : The Persian knowledge graph

Editors: Mayank Kejriwal, Vanessa Lopez, Juan F. Sequeda Authors: Majid Asgari-Bidhendi, Ali Hadian, Behrouz Minaei-BidgoliAuthors Info & Claims

Semantic Web, Volume 10, Issue 6

Pages 1169 - 1196

https://doi.org/10.3233/SW-190369

Published: 01 January 2019 Publication History

Abstract

Over the last decade, extensive research has been done on automatic construction of knowledge graphs from Web resources, resulting in a number of large-scale knowledge graphs such as YAGO, DBpedia, BabelNet, and Wikidata. Despite that some of these knowledge graphs are multilingual, they contain few or no linked data in Persian, and do not support tools for extracting knowledge from Persian information sources. FarsBase (available at http://farsbase.net/about) is the first Persian multi-source knowledge graph, which is specifically designed for semantic search engines to support Persian knowledge. FarsBase uses a diverse set of hybrid and flexible techniques to extract and integrate knowledge from various sources, such as Wikipedia, Web tables and unstructured texts. It also supports entity linking, which allows integration with other knowledge graphs. To maintain high accuracy for triples, we adopt a low-cost mechanism for verifying candidate knowledge by human experts, where the candidates for human verification are prioritized using different heuristics. FarsBase is being used as the semantic-search system of a Persian search engine and efficiently answers hundreds of semantic queries per second.

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Cited By

Boroujeni GFaili HYaghoobzadeh YAlam MBuscaldi DCochez MOsborne FRefogiato Recupero DSack H(2022)Answer selection in community question answering exploiting knowledge graph and context informationSemantic Web10.3233/SW-22297013:3(339-356)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/SW-222970

Index Terms

FarsBase: The Persian knowledge graph
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Information systems
  1. Information retrieval

Index terms have been assigned to the content through auto-classification.

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cover image Semantic Web

Semantic Web Volume 10, Issue 6

Knowledge Graphs: Construction, Management and Querying

2019

234 pages

ISSN:1570-0844

EISSN:2210-4968

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© 2019 – IOS Press and the authors. All rights reserved.

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Published: 01 January 2019

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Boroujeni GFaili HYaghoobzadeh YAlam MBuscaldi DCochez MOsborne FRefogiato Recupero DSack H(2022)Answer selection in community question answering exploiting knowledge graph and context informationSemantic Web10.3233/SW-22297013:3(339-356)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/SW-222970

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