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- W2184861421 abstract "Research in text summarization is predominantly tar gets on measure of the worth of sentences for a summary. The proposed work has associated the Deep learning algorithm with fuzzy logic to improve the efficiency of the generated summary. The proposed work has two phases, they are training phase and testing phases. The training phase utilized to extr act the benefits of fuzzy logic and deep learning a lgorithm for the efficient summary generation. Similar to ev ery training phase, the proposed training phases is also possessed with well known data and attributes. Latt er to the training phase, the testing phases is implemented to check the efficiency of the proposed approach. The experimental evaluation of the proposed work provided the predictable results as, the average precision obtained is 0.37, the average recall is 0.86 and the average f-measure is obtained as 0. 50%." @default.
- W2184861421 created "2016-06-24" @default.
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- W2184861421 date "2014-01-01" @default.
- W2184861421 modified "2023-09-27" @default.
- W2184861421 title "ASSOCIATION OF DEEP LEARNING ALGORITHM WITH FUZZY LOGIC FOR MULTIDOCUMENT TEXT SUMMARIZATION" @default.
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