The world is overloaded with information due to the internet revolution. This calls for an efficient and accurate summarization system to extract relevant information. Text summarization system automatically generates a summary of a given document and helps people to take effective decisions in less time. In this book two methods have been proposed for query-focused multi-document summarization that uses k-mean clustering and term-frequency-inverse-sentence-frequency method for sentence weighting to rank the sentences of the document(s) with respect to a given query. The proposed methods find the proximity of documents and query, and later uses this proximity to rank sentences of each document. A comparative study for proposed methods has been done and experimental results shows that both methods are comparable because of a slight difference in performance. DUC 2007 test dataset and ROUGH-1.5.5 summarization evaluation package is used for evaluation purpose.
|Number of Pages||100|
|Book Type||Computer networking & communications|
|Country of Manufacture||India|
|Product Brand||LAP LAMBERT Academic Publishing|
|Product Packaging Info||Box|
|In The Box||1 Piece|
|Product First Available On ClickOnCare.com||2015-07-08 00:00:00|