Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy

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Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy
Authors
Liang Zheng
Publication date
2011
Links
Original

Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy - scientific work related to Wikipedia quality published in 2011, written by Liang Zheng.

Overview

Any attempt to compute semantics relatedness of natural language words needs a lot of background knowledge.Studies have shown that Wikipedia,which is the largest encyclopedia and could be used not only as a corpus but also a knowledge base with rich semantic information,is the ideal resource for semantic computation.In this paper,a new algorithm based on Wikipedia links and taxonomy is proposed to compute semantic relatedness of words.Since the algorithm uses only Wikipedia link structure and taxonomy,there is no need for complex text processing and the computation overhead required is smaller.Tests on a number of manual defined data sets show that it′s better than algorithms only based on Wikipedia links or on Wikipedia taxonomy.In the best case,the Spearman correlation coefficient has been increased 30.96%.

Embed

Wikipedia Quality

Zheng, Liang. (2011). "[[Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy]]".

English Wikipedia

{{cite journal |last1=Zheng |first1=Liang |title=Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy |date=2011 |url=https://wikipediaquality.com/wiki/Computing_Semantic_Relatedness_Using_Chinese_Wikipedia_Links_and_Taxonomy}}

HTML

Zheng, Liang. (2011). &quot;<a href="https://wikipediaquality.com/wiki/Computing_Semantic_Relatedness_Using_Chinese_Wikipedia_Links_and_Taxonomy">Computing Semantic Relatedness Using Chinese Wikipedia Links and Taxonomy</a>&quot;.