Paper Info
Title
SITAC: discovering semantically identical temporally altering concepts in text archives
Abstract
This paper demonstrates a system called SITAC based on our proposed approach to automate the discovery of concepts (called SITACs) in text sources that are identical semantically but alter their names over time. This system is developed to perform time-aware translation of queries over text corpora by incorporating terminology evolution, thus providing more accurate responses to users, e.g., query processing on Mumbai should automatically take into account its former name Bombay. The SITAC system constitutes a novel collaborative framework of natural language processing, association rule mining and contextual similarity.
Year
DOI
Venue
2011
10.1145/1951365.1951442
Extending Database Technology
Keywords
Field
DocType
identical semantically,text corpus,sitac system,natural language processing,association rule mining,accurate response,text archives,contextual similarity,former name,semantically identical temporally,query processing,text source,association rule,ranking,association rules,information retrieval,text mining
Data mining,Text mining,Ranking,Information retrieval,Terminology,Computer science,Text corpus,Former name,Association rule learning,Natural language processing,Artificial intelligence,Database
Conference
Citations 
PageRank 
References 
6
0.44
7
Authors
4
Name
Order
Citations
PageRank
Amal Chaminda Kaluarachchi160.44
Debjani Roychoudhury260.44
Aparna S. Varde318828.71
Gerhard Weikum4127102146.01