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Mining Acronym Expansion from Web


Affiliations
1 Dept of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, India
     

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Acronyms are extensively used in web search. Typically acronym is an ambiguous one, when a user gives acronym as search query the search engine returns the results even it is not related to the user intent. To address this problem a method is proposed in this paper that, how to get the user desired web pages of the given acronym search query. The method uses two approaches they are i. Discover all multifarious definitions for the given acronym query ii. Finding popularity score and context words of each acronym definition. Acronym definitions are extracted from Google snippets, titles and acronym finder. Popularity score and context words are identified from query log files. The results evince that the proposed method performance is better than the existing system.


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Abstract Views: 167

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  • Mining Acronym Expansion from Web

Abstract Views: 167  |  PDF Views: 3

Authors

R. Menaha
Dept of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, India
J. Meenaakshi
Dept of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, India
P. Mohanapriya
Dept of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, India
V. Nandhini
Dept of Information Technology, Dr. Mahalingam College of Engineering and Technology, Pollachi, India

Abstract


Acronyms are extensively used in web search. Typically acronym is an ambiguous one, when a user gives acronym as search query the search engine returns the results even it is not related to the user intent. To address this problem a method is proposed in this paper that, how to get the user desired web pages of the given acronym search query. The method uses two approaches they are i. Discover all multifarious definitions for the given acronym query ii. Finding popularity score and context words of each acronym definition. Acronym definitions are extracted from Google snippets, titles and acronym finder. Popularity score and context words are identified from query log files. The results evince that the proposed method performance is better than the existing system.