Difference between revisions of "An Exploratory Study of Navigating Wikipedia Semantically: Model and Application"
(Infobox) |
(+ Embed) |
||
Line 10: | Line 10: | ||
== Overview == | == Overview == | ||
Due to the popularity of link-based applications like [[Wikipedia]], one of the most important issues in online research is how to alleviate information overload on the World Wide Web (WWW) and facilitate effective information-seeking. To address the problem, authors propose a semantically-based navigation application that is based on the theories and techniques of link mining, semantic [[relatedness]] analysis and text summarization. Authors goal is to develop an application that assists users in efficiently finding the related subtopics for a seed query and then quickly checking the content of articles. Authors establish a topic network by analyzing the internal links of Wikipedia and applying the Normalized [[Google]] Distance algorithm in order to quantify the strength of the semantic relationships between articles via key terms. To help users explore and read topic-related articles, authors propose a SNA-based summarization approach to summarize articles. To visualize the topic network more efficiently, authors develop a semantically-based WikiMap to help users navigate Wikipedia effectively. | Due to the popularity of link-based applications like [[Wikipedia]], one of the most important issues in online research is how to alleviate information overload on the World Wide Web (WWW) and facilitate effective information-seeking. To address the problem, authors propose a semantically-based navigation application that is based on the theories and techniques of link mining, semantic [[relatedness]] analysis and text summarization. Authors goal is to develop an application that assists users in efficiently finding the related subtopics for a seed query and then quickly checking the content of articles. Authors establish a topic network by analyzing the internal links of Wikipedia and applying the Normalized [[Google]] Distance algorithm in order to quantify the strength of the semantic relationships between articles via key terms. To help users explore and read topic-related articles, authors propose a SNA-based summarization approach to summarize articles. To visualize the topic network more efficiently, authors develop a semantically-based WikiMap to help users navigate Wikipedia effectively. | ||
+ | |||
+ | == Embed == | ||
+ | === Wikipedia Quality === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Wu, I-Chin; Lin, Yi-Sheng; Liu, Che-Hung. (2011). "[[An Exploratory Study of Navigating Wikipedia Semantically: Model and Application]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21796-8_15. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === English Wikipedia === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | {{cite journal |last1=Wu |first1=I-Chin |last2=Lin |first2=Yi-Sheng |last3=Liu |first3=Che-Hung |title=An Exploratory Study of Navigating Wikipedia Semantically: Model and Application |date=2011 |doi=10.1007/978-3-642-21796-8_15 |url=https://wikipediaquality.com/wiki/An_Exploratory_Study_of_Navigating_Wikipedia_Semantically:_Model_and_Application |journal=Springer, Berlin, Heidelberg}} | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === HTML === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Wu, I-Chin; Lin, Yi-Sheng; Liu, Che-Hung. (2011). &quot;<a href="https://wikipediaquality.com/wiki/An_Exploratory_Study_of_Navigating_Wikipedia_Semantically:_Model_and_Application">An Exploratory Study of Navigating Wikipedia Semantically: Model and Application</a>&quot;. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21796-8_15. | ||
+ | </nowiki> | ||
+ | </code> |
Revision as of 08:59, 20 October 2019
Authors | I-Chin Wu Yi-Sheng Lin Che-Hung Liu |
---|---|
Publication date | 2011 |
DOI | 10.1007/978-3-642-21796-8_15 |
Links | Original |
An Exploratory Study of Navigating Wikipedia Semantically: Model and Application - scientific work related to Wikipedia quality published in 2011, written by I-Chin Wu, Yi-Sheng Lin and Che-Hung Liu.
Overview
Due to the popularity of link-based applications like Wikipedia, one of the most important issues in online research is how to alleviate information overload on the World Wide Web (WWW) and facilitate effective information-seeking. To address the problem, authors propose a semantically-based navigation application that is based on the theories and techniques of link mining, semantic relatedness analysis and text summarization. Authors goal is to develop an application that assists users in efficiently finding the related subtopics for a seed query and then quickly checking the content of articles. Authors establish a topic network by analyzing the internal links of Wikipedia and applying the Normalized Google Distance algorithm in order to quantify the strength of the semantic relationships between articles via key terms. To help users explore and read topic-related articles, authors propose a SNA-based summarization approach to summarize articles. To visualize the topic network more efficiently, authors develop a semantically-based WikiMap to help users navigate Wikipedia effectively.
Embed
Wikipedia Quality
Wu, I-Chin; Lin, Yi-Sheng; Liu, Che-Hung. (2011). "[[An Exploratory Study of Navigating Wikipedia Semantically: Model and Application]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21796-8_15.
English Wikipedia
{{cite journal |last1=Wu |first1=I-Chin |last2=Lin |first2=Yi-Sheng |last3=Liu |first3=Che-Hung |title=An Exploratory Study of Navigating Wikipedia Semantically: Model and Application |date=2011 |doi=10.1007/978-3-642-21796-8_15 |url=https://wikipediaquality.com/wiki/An_Exploratory_Study_of_Navigating_Wikipedia_Semantically:_Model_and_Application |journal=Springer, Berlin, Heidelberg}}
HTML
Wu, I-Chin; Lin, Yi-Sheng; Liu, Che-Hung. (2011). "<a href="https://wikipediaquality.com/wiki/An_Exploratory_Study_of_Navigating_Wikipedia_Semantically:_Model_and_Application">An Exploratory Study of Navigating Wikipedia Semantically: Model and Application</a>". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21796-8_15.