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License: CC BY NC
Data sources: UnpayWall
https://doi.org/10.2991/csss-1...
Article . 2014 . Peer-reviewed
Data sources: Crossref
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Disambiguating named entities by semantic web

Authors: Koohpeyma Fateme; Azari Ideh;

Disambiguating named entities by semantic web

Abstract

There are many words in natural language sentences which describe an object or event in real world. An important step to understand a sentence is finding the exact meaning of all words. In this paper we propose an approach to identify meaning of each named entity of a text by using web of data (LOD) as a large scale knowledge base. The proposed approach is referencing named entities to suitable URIs of web of data. It compares the context of the text with RDF graphs retrieved from the web and then select URIs which have maximum agreement with named entities of the text. Experimental Results show that our approach outperforms previous works in terms of accuracy and Precision on Wikipedia articles.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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