Difference between revisions of "Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network"

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{{Infobox work
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| title = Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network
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| date = 2011
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| authors = [[Cheng-Yu Lu]]<br />[[Shou-Wei Ho]]<br />[[Jen-Ming Chung]]<br />[[Fu-Yuan Hsu]]<br />[[Hahn-Ming Lee]]<br />[[Jan-Ming Ho]]
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| doi = 10.1109/WI-IAT.2011.140
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| link = http://www.ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06040852
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| plink = https://www.semanticscholar.org/paper/Mining-Fuzzy-Domain-Ontology-Based-on-Concept-from-Lu-Ho/03026b81147d4979026e86d572f035484d5e2ff9/figure/2
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}}
 
'''Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network''' - scientific work related to [[Wikipedia quality]] published in 2011, written by [[Cheng-Yu Lu]], [[Shou-Wei Ho]], [[Jen-Ming Chung]], [[Fu-Yuan Hsu]], [[Hahn-Ming Lee]] and [[Jan-Ming Ho]].
 
'''Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network''' - scientific work related to [[Wikipedia quality]] published in 2011, written by [[Cheng-Yu Lu]], [[Shou-Wei Ho]], [[Jen-Ming Chung]], [[Fu-Yuan Hsu]], [[Hahn-Ming Lee]] and [[Jan-Ming Ho]].
  
 
== Overview ==
 
== Overview ==
 
Ontology is essential in the formalization of domain knowledge for effective human-computer interactions (i.e., expert-finding). Many researchers have proposed approaches to measure the similarity between concepts by accessing fuzzy domain [[ontology]]. However, engineering of the construction of domain ontologies turns out to be labor intensive and tedious. In this paper, authors propose an approach to mine domain concepts from [[Wikipedia]] Category Network, and to generate the fuzzy relation based on a concept vector extraction method to measure the [[relatedness]] between a single term and a concept. Authors methodology can conceptualize domain knowledge by mining Wikipedia Category Network. An empirical experiment is conducted to evaluate the robustness by using TREC dataset. Experiment results show the constructed fuzzy domain ontology derived by proposed approach can discover robust fuzzy domain ontology with satisfactory accuracy in [[information retrieval]] tasks.
 
Ontology is essential in the formalization of domain knowledge for effective human-computer interactions (i.e., expert-finding). Many researchers have proposed approaches to measure the similarity between concepts by accessing fuzzy domain [[ontology]]. However, engineering of the construction of domain ontologies turns out to be labor intensive and tedious. In this paper, authors propose an approach to mine domain concepts from [[Wikipedia]] Category Network, and to generate the fuzzy relation based on a concept vector extraction method to measure the [[relatedness]] between a single term and a concept. Authors methodology can conceptualize domain knowledge by mining Wikipedia Category Network. An empirical experiment is conducted to evaluate the robustness by using TREC dataset. Experiment results show the constructed fuzzy domain ontology derived by proposed approach can discover robust fuzzy domain ontology with satisfactory accuracy in [[information retrieval]] tasks.

Latest revision as of 02:56, 24 May 2020


Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network
Authors
Cheng-Yu Lu
Shou-Wei Ho
Jen-Ming Chung
Fu-Yuan Hsu
Hahn-Ming Lee
Jan-Ming Ho
Publication date
2011
DOI
10.1109/WI-IAT.2011.140
Links
Original Preprint

Mining Fuzzy Domain Ontology based on Concept Vector from Wikipedia Category Network - scientific work related to Wikipedia quality published in 2011, written by Cheng-Yu Lu, Shou-Wei Ho, Jen-Ming Chung, Fu-Yuan Hsu, Hahn-Ming Lee and Jan-Ming Ho.

Overview

Ontology is essential in the formalization of domain knowledge for effective human-computer interactions (i.e., expert-finding). Many researchers have proposed approaches to measure the similarity between concepts by accessing fuzzy domain ontology. However, engineering of the construction of domain ontologies turns out to be labor intensive and tedious. In this paper, authors propose an approach to mine domain concepts from Wikipedia Category Network, and to generate the fuzzy relation based on a concept vector extraction method to measure the relatedness between a single term and a concept. Authors methodology can conceptualize domain knowledge by mining Wikipedia Category Network. An empirical experiment is conducted to evaluate the robustness by using TREC dataset. Experiment results show the constructed fuzzy domain ontology derived by proposed approach can discover robust fuzzy domain ontology with satisfactory accuracy in information retrieval tasks.