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ABSTRACT
Title |
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Multi-document Summarization for Query Answering E-learning System |
Authors |
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Dr.S.Saraswathi, S.Janani, M.Hemamalini, V.Priyadharshini |
Keywords |
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Tagger, Multi-document Summarization, Information Extraction and Retrieval, Ontological tree, Concept-wise retrieval. |
Issue Date |
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March 2011. |
Abstract |
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The proposed E-learning system aims at providing a multi-document summarization for documents retrieved from Google and providing the user a precise answer for his/her query under the domain of “Operating Systems”. This E-learning system also provides documents display for various topics, authentication facility for it to be used by certain users. Authenticity of users is maintained by Symmetric Encryption key Algorithm. The system is designed in a manner that the query entered by the user is passed to the tree tagger to obtain the keywords which are then passed to Google to retrieve multiple documents. Multiple levels of summarization are performed on the documents to retrieve exact answer for the user. Document ranking is performed by using tf*idf weights followed by Individual document summarization using keywords and concept words. The similarity of documents is then compared to produce a non-redundant output. Finally the resultant data is submitted to the user. |
Page(s) |
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1147-1154 |
ISSN |
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0975–3397 |
Source |
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Vol. 3, Issue.03 |
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