TY  - JOUR
T1  - An Event Graph Based Document Representation for Information Retrieval and Summarazing the Text Based on Events
AU - Janarthanan, P. AU - Ramachandran, V. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 18
SP  - 3531
EP  - 3537
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.3531.3537
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.3531.3537
KW  - Information Retrieval (IR)
KW  -event graph
KW  -machine learning
KW  -rule based models
KW  -query
AB  - Most of information retrieval and text summarization methods does not describing about the
semantics of events and these methods rely only on shallow document representation. The current problem
of Information retrieval is that query given by the user is not the same as the one by which the information has
been indexed. It is exceptionally hard to locate the required data and relevant document. Hence, structuring
the queries and documents in terms of event graph using supervised machine learning and rule based model
and employ graph kernels for query document similarity.
ER  -