@article{MAKHILLAJIT201615186379,
    title = {An Event Graph Based Document Representation for Information Retrieval and Summarazing the Text Based on Events},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {18},
    pages = {3531-3537},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.3531.3537},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.3531.3537},
    author = {P. and},
    keywords = {Information Retrieval (IR),event graph,machine learning,rule based models,query},
    abstract = {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.}
    }