DocumentCode
627358
Title
Application of data mining for identifying topics at the document level
Author
Reza, Marifa Farzin ; Matin, Rizwana
Author_Institution
Comput. Sci. & Eng., BRAC Univ., Dhaka, Bangladesh
fYear
2013
fDate
17-18 May 2013
Firstpage
1
Lastpage
6
Abstract
Data mining techniques are very popular in modern days and are used in NLP (Natural Language Processing). It allows users to analyze data from many different perspectives, categorize it, and summarize the relationships identified. One of the techniques, clustering items to groups, has been very popular. We use this technique here to find different topics in a document. We aim to replicate previous results and empirically verify this measure to identify hypothetical topic boundaries.
Keywords
data mining; document handling; natural language processing; pattern clustering; NLP; data mining; document level topic identification; hypothetical topic boundaries; item clustering; natural language processing; Clustering algorithms; Data mining; Natural language processing; Noise; Prediction algorithms; Speech; Unsupervised learning; Artificial intelligence; Data-mining; Natural language Processing (NLP); Unsupervised Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Informatics, Electronics & Vision (ICIEV), 2013 International Conference on
Conference_Location
Dhaka
Print_ISBN
978-1-4799-0397-9
Type
conf
DOI
10.1109/ICIEV.2013.6572712
Filename
6572712
Link To Document