Browse wiki

Jump to: navigation, search
An n-gram and initial description based approach for entity ranking track
Abstract The most important work that takes the cenThe most important work that takes the center stage in the Entity Ranking track of INEX is proper query formation. Both the subtasks, namely Entity Ranking and List Completion, would immensely benefit if the given query can be expanded with more relevant terms, thereby improving the efficiency of the search engine. This paper stresses on the correct identification of "Meaningful n-grams" from the given title and proper selection of the "Prominent n-grams" among them as the utmost important task that improves query formation and hence improves the efficiencies of the overall Entity Ranking tasks. We also exploit the Initial Descriptions (IDES) of the Wikipedia articles for ranking the retrieved answers based on their similarities with the given topic. List completion task is further aided by the related Wikipedia articles that boosted the score of retrieved answers.at boosted the score of retrieved answers.
Abstractsub The most important work that takes the cenThe most important work that takes the center stage in the Entity Ranking track of INEX is proper query formation. Both the subtasks, namely Entity Ranking and List Completion, would immensely benefit if the given query can be expanded with more relevant terms, thereby improving the efficiency of the search engine. This paper stresses on the correct identification of "Meaningful n-grams" from the given title and proper selection of the "Prominent n-grams" among them as the utmost important task that improves query formation and hence improves the efficiencies of the overall Entity Ranking tasks. We also exploit the Initial Descriptions (IDES) of the Wikipedia articles for ranking the retrieved answers based on their similarities with the given topic. List completion task is further aided by the related Wikipedia articles that boosted the score of retrieved answers.at boosted the score of retrieved answers.
Bibtextype inproceedings  +
Doi 10.1007/978-3-540-85902-4_26  +
Has author Murugeshan M.S. + , Saswati Mukherjee +
Has extra keyword Computer software + , Information management + , Information services + , Search engine + , XML + , Entity Ranking + , List Completion + , N-gram checking + , N-grams + , Query formation + , Sub-tasks + , Wikipedia + , XML documents + , XML Retrieval + , Markup languages +
Has keyword Entity Ranking + , List Completion + , N-gram checking +
Isbn 3540859012; 9783540859017  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 293–305  +
Published in Lecture Notes in Computer Science +
Title An n-gram and initial description based approach for entity ranking track +
Type conference paper  +
Volume 4862 LNCS  +
Year 2008 +
Creation dateThis property is a special property in this wiki. 7 November 2014 01:47:17  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 01:47:17  +
DateThis property is a special property in this wiki. 2008  +
hide properties that link here 
An n-gram and initial description based approach for entity ranking track + Title
 

 

Enter the name of the page to start browsing from.