Difference between revisions of "Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia"

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== Overview ==
 
== Overview ==
 
This work introduces a semantics-based navigation application called WNavi s . It facilitates informationseeking activities in internal link-based websites within [[Wikipedia]]. Authors goal is to develop an application that helps users easily find related articles on a given topic and then quickly check the content of articles to explore concepts in Wikipedia. Authors constructed a subject-based network by analyzing the internal links of Wikipedia and applying a semantic [[relatedness]] analysis to measure the strength of the semantic relationships between articles. In order to locate specific information and enable users to quickly explore and read subject-related articles, authors propose a [[social network]] analysis (SNA)-based topic summarization technique that extracts meaningful sentences from articles. Authors applied a number of intrinsic evaluation methods to demonstrate the efficacy of the summarization techniques. Authors findings have implications for the design of a navigation tool that can help users explore topics and increase their subject knowledge.
 
This work introduces a semantics-based navigation application called WNavi s . It facilitates informationseeking activities in internal link-based websites within [[Wikipedia]]. Authors goal is to develop an application that helps users easily find related articles on a given topic and then quickly check the content of articles to explore concepts in Wikipedia. Authors constructed a subject-based network by analyzing the internal links of Wikipedia and applying a semantic [[relatedness]] analysis to measure the strength of the semantic relationships between articles. In order to locate specific information and enable users to quickly explore and read subject-related articles, authors propose a [[social network]] analysis (SNA)-based topic summarization technique that extracts meaningful sentences from articles. Authors applied a number of intrinsic evaluation methods to demonstrate the efficacy of the summarization techniques. Authors findings have implications for the design of a navigation tool that can help users explore topics and increase their subject knowledge.
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== Embed ==
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=== Wikipedia Quality ===
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Wu, I-Chin; Tsai, Chi-Hong; Lin, Yu-Hsuan. (2013). "[[Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia]]".DOI: 10.1109/IRI.2013.6642458.
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=== English Wikipedia ===
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{{cite journal |last1=Wu |first1=I-Chin |last2=Tsai |first2=Chi-Hong |last3=Lin |first3=Yu-Hsuan |title=Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia |date=2013 |doi=10.1109/IRI.2013.6642458 |url=https://wikipediaquality.com/wiki/Clustering_and_Summarization_Topics_of_Subject_Knowledge_Through_Analyzing_Internal_Links_of_Wikipedia}}
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=== HTML ===
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Wu, I-Chin; Tsai, Chi-Hong; Lin, Yu-Hsuan. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Clustering_and_Summarization_Topics_of_Subject_Knowledge_Through_Analyzing_Internal_Links_of_Wikipedia">Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia</a>&amp;quot;.DOI: 10.1109/IRI.2013.6642458.
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Revision as of 08:05, 14 January 2021


Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia
Authors
I-Chin Wu
Chi-Hong Tsai
Yu-Hsuan Lin
Publication date
2013
DOI
10.1109/IRI.2013.6642458
Links
Original

Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia - scientific work related to Wikipedia quality published in 2013, written by I-Chin Wu, Chi-Hong Tsai and Yu-Hsuan Lin.

Overview

This work introduces a semantics-based navigation application called WNavi s . It facilitates informationseeking activities in internal link-based websites within Wikipedia. Authors goal is to develop an application that helps users easily find related articles on a given topic and then quickly check the content of articles to explore concepts in Wikipedia. Authors constructed a subject-based network by analyzing the internal links of Wikipedia and applying a semantic relatedness analysis to measure the strength of the semantic relationships between articles. In order to locate specific information and enable users to quickly explore and read subject-related articles, authors propose a social network analysis (SNA)-based topic summarization technique that extracts meaningful sentences from articles. Authors applied a number of intrinsic evaluation methods to demonstrate the efficacy of the summarization techniques. Authors findings have implications for the design of a navigation tool that can help users explore topics and increase their subject knowledge.

Embed

Wikipedia Quality

Wu, I-Chin; Tsai, Chi-Hong; Lin, Yu-Hsuan. (2013). "[[Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia]]".DOI: 10.1109/IRI.2013.6642458.

English Wikipedia

{{cite journal |last1=Wu |first1=I-Chin |last2=Tsai |first2=Chi-Hong |last3=Lin |first3=Yu-Hsuan |title=Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia |date=2013 |doi=10.1109/IRI.2013.6642458 |url=https://wikipediaquality.com/wiki/Clustering_and_Summarization_Topics_of_Subject_Knowledge_Through_Analyzing_Internal_Links_of_Wikipedia}}

HTML

Wu, I-Chin; Tsai, Chi-Hong; Lin, Yu-Hsuan. (2013). &quot;<a href="https://wikipediaquality.com/wiki/Clustering_and_Summarization_Topics_of_Subject_Knowledge_Through_Analyzing_Internal_Links_of_Wikipedia">Clustering and Summarization Topics of Subject Knowledge Through Analyzing Internal Links of Wikipedia</a>&quot;.DOI: 10.1109/IRI.2013.6642458.