Difference between revisions of "Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia"

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== Overview ==
 
== Overview ==
 
Query log analysis can provide valuable information for improving [[information retrieval]] performance. This paper reports findings from a query log mining project, in which query terms falling in the very long tail of low to zero similarity (with the controlled vocabulary) scores were analyzed by using similarity algorithms. The query log data was collected from the Gateway to Educational Materials (GEM). The limited number of terms in the GEM controlled vocabulary was a major source for the long tail of low or zero similarity scores for the query terms. To mitigate this limitation, authors employed a strategy that involved using the general-purpose (domain-independent) [[ontology]] [[WordNet]] and community-created [[Wikipedia]] as the bridge to establish semantic [[relatedness]] between GEM controlled vocabulary (as well as new concept classes identified by human experts) and user query terms. The two sources, WordNet and Wikipedia, were complementary in mapping different types of query terms. A combination of both sources achieved a modest rate of mapping accuracy. The paper discussed the implications of the findings for automatic semantic analysis and vocabulary development and validation.
 
Query log analysis can provide valuable information for improving [[information retrieval]] performance. This paper reports findings from a query log mining project, in which query terms falling in the very long tail of low to zero similarity (with the controlled vocabulary) scores were analyzed by using similarity algorithms. The query log data was collected from the Gateway to Educational Materials (GEM). The limited number of terms in the GEM controlled vocabulary was a major source for the long tail of low or zero similarity scores for the query terms. To mitigate this limitation, authors employed a strategy that involved using the general-purpose (domain-independent) [[ontology]] [[WordNet]] and community-created [[Wikipedia]] as the bridge to establish semantic [[relatedness]] between GEM controlled vocabulary (as well as new concept classes identified by human experts) and user query terms. The two sources, WordNet and Wikipedia, were complementary in mapping different types of query terms. A combination of both sources achieved a modest rate of mapping accuracy. The paper discussed the implications of the findings for automatic semantic analysis and vocabulary development and validation.
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=== Wikipedia Quality ===
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Liu, Xiaozhong; Qin, Jian; Chen, Miao; Park, Ji Hong. (2009). "[[Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia]]". Wiley Subscription Services, Inc., A Wiley Company. DOI: 10.1002/meet.2008.1450450286.
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=== English Wikipedia ===
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{{cite journal |last1=Liu |first1=Xiaozhong |last2=Qin |first2=Jian |last3=Chen |first3=Miao |last4=Park |first4=Ji Hong |title=Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia |date=2009 |doi=10.1002/meet.2008.1450450286 |url=https://wikipediaquality.com/wiki/Automatic_Semantic_Mapping_Between_Query_Terms_and_Controlled_Vocabulary_Through_Using_Wordnet_and_Wikipedia |journal=Wiley Subscription Services, Inc., A Wiley Company}}
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Liu, Xiaozhong; Qin, Jian; Chen, Miao; Park, Ji Hong. (2009). &amp;quot;<a href="https://wikipediaquality.com/wiki/Automatic_Semantic_Mapping_Between_Query_Terms_and_Controlled_Vocabulary_Through_Using_Wordnet_and_Wikipedia">Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia</a>&amp;quot;. Wiley Subscription Services, Inc., A Wiley Company. DOI: 10.1002/meet.2008.1450450286.
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Revision as of 06:49, 25 January 2021


Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia
Authors
Xiaozhong Liu
Jian Qin
Miao Chen
Ji Hong Park
Publication date
2009
DOI
10.1002/meet.2008.1450450286
Links
Original Preprint

Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia - scientific work related to Wikipedia quality published in 2009, written by Xiaozhong Liu, Jian Qin, Miao Chen and Ji Hong Park.

Overview

Query log analysis can provide valuable information for improving information retrieval performance. This paper reports findings from a query log mining project, in which query terms falling in the very long tail of low to zero similarity (with the controlled vocabulary) scores were analyzed by using similarity algorithms. The query log data was collected from the Gateway to Educational Materials (GEM). The limited number of terms in the GEM controlled vocabulary was a major source for the long tail of low or zero similarity scores for the query terms. To mitigate this limitation, authors employed a strategy that involved using the general-purpose (domain-independent) ontology WordNet and community-created Wikipedia as the bridge to establish semantic relatedness between GEM controlled vocabulary (as well as new concept classes identified by human experts) and user query terms. The two sources, WordNet and Wikipedia, were complementary in mapping different types of query terms. A combination of both sources achieved a modest rate of mapping accuracy. The paper discussed the implications of the findings for automatic semantic analysis and vocabulary development and validation.

Embed

Wikipedia Quality

Liu, Xiaozhong; Qin, Jian; Chen, Miao; Park, Ji Hong. (2009). "[[Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia]]". Wiley Subscription Services, Inc., A Wiley Company. DOI: 10.1002/meet.2008.1450450286.

English Wikipedia

{{cite journal |last1=Liu |first1=Xiaozhong |last2=Qin |first2=Jian |last3=Chen |first3=Miao |last4=Park |first4=Ji Hong |title=Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia |date=2009 |doi=10.1002/meet.2008.1450450286 |url=https://wikipediaquality.com/wiki/Automatic_Semantic_Mapping_Between_Query_Terms_and_Controlled_Vocabulary_Through_Using_Wordnet_and_Wikipedia |journal=Wiley Subscription Services, Inc., A Wiley Company}}

HTML

Liu, Xiaozhong; Qin, Jian; Chen, Miao; Park, Ji Hong. (2009). &quot;<a href="https://wikipediaquality.com/wiki/Automatic_Semantic_Mapping_Between_Query_Terms_and_Controlled_Vocabulary_Through_Using_Wordnet_and_Wikipedia">Automatic Semantic Mapping Between Query Terms and Controlled Vocabulary Through Using Wordnet and Wikipedia</a>&quot;. Wiley Subscription Services, Inc., A Wiley Company. DOI: 10.1002/meet.2008.1450450286.