[PDF] Top 20 An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning
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An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning
... a multi-document summary possesses some notable merits over a single-document ...topic based on a document set representing identical information in several documents, distinct ... See full document
5
A Machine Learning Approach to Sentence Ordering for Multidocument Summarization and Its Evaluation
... format, automatic text summarization has become ...the document set may contain repeating information as well as contradictory information and these challenges should be considered when extracting ... See full document
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A New Approach to Automatic Document Summarization
... Abstract-based summarization never goes beyond conceptual stage, though ever since the dawn of summarization it has been argued as an alternative for its extract-based ...extractive ... See full document
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Study on Multi Document Summarization by Machine Learning Technique for Clustered Documents
... of multi document summarization by using different approach like abstractive-extractive summarization ...approach. Multi document summarization is a ... See full document
5
Machine Learning Techniques for Document Summarization: A Survey
... an approach that uses lexical and semantic, both sentence reduction ...techniques. Summarization is done in two phases, first clustering by similarity and then clustering by ...sentence based on the ... See full document
6
Multi-Document Summarization using Automatic Key-Phrase Extraction
... successful multi-document summarization systems follow the extractive summarization ...original document set and then select the most salient sentences to compose summaries for a good ... See full document
8
Fear the REAPER: A System for Automatic Multi Document Summarization with Reinforcement Learning
... automated multi- document summarization (Mani, 2001) is to se- lect a subset of textual units, in this case sentences, from the source document cluster to form a sum- mary of the cluster in ... See full document
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Towards Multi Document Summarization of Scientific Articles:Making Interesting Comparisons with SciSumm
... our multi-document sum- mary from the text closest to the ...a summarization ap- proach that can be seen as the converse of what we are working to ...clustering approach over different ... See full document
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A Multi Document Multi Lingual Automatic Summarization System
... of multi-document text summarization, a collection of input documents about a particular subject is received from the user and a coherent summary without redundant infor- mation is ...new ... See full document
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Query focused Multi Document Summarization: Combining a Topic Model with Graph based Semi supervised Learning
... our summarization approach is to discover the latent topics and cluster sentences according to the ...(4) Document-specific words that are local to a single document and do not appear across ... See full document
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A Query Focused Multi Document Automatic Summarization
... original document, thus eliminating the source bias due to individual writing style of human ...summary, based on how coherent it is with the (p-1)th ... See full document
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Automatic Evaluation of Linguistic Quality in Multi Document Summarization
... five automatic summarizers were used in these ...and machine-produced sum- maries, so the results may be influenced by the ease of discriminating between a human and ma- chine written ...for ... See full document
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Extractive Summarization Using Multi Task Learning with Document Classification
... for automatic document summarization that can be implement in practical scenarios is in- creasing (Li et ...extractive summarization ap- proaches (Erkan and Radev, 2004; McDonald, 2007; Wong ... See full document
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A Semantic Based Approach for Abstractive Multi-Document Text Summarization
... Text Summarization has become a very popular Natural Language Processing (NLP) task in recent ...Internet, automatic summarization has been developed and improved in order to help users manage all ... See full document
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Fast Concept Mention Grouping for Concept Map based Multi Document Summarization
... combined approach (LSH-CW ) by substi- tuting them into that ...by concept F1-score after grouping and tune the SVM with cross-validation only for the three best settings, leading to the parameters d = 200, ... See full document
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Supervised Learning of Automatic Pyramid for Optimization Based Multi Document Summarization
... maries based on human ...is based on a manual comparison of Summary Content Units (SCUs) in reference sum- maries against SCUs in system ...for automatic Pyra- mid scoring called PEAK, which uses ... See full document
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Concept Map Based Multi Document Summarization using Concept Coreference Resolution and Global Importance Optimization
... summary concept map that is connected, does not exceed the target size and con- tains as many important concepts as possible, we are only aware of a heuristic approach suggested by Zubrinic et ...to ... See full document
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Using External Resources and Joint Learning for Bigram Weighting in ILP Based Multi Document Summarization
... First, using external resources contributes to the im- proved performance of our method compared to oth- ers that only use internal ...the summarization task needs to have a deeper “understanding” of a ... See full document
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Query-Focused Multi-Document Summarization Using Co-Training Based Semi-Supervised Learning
... proposed approach first makes full use of the co-training algorithm to identify the relevant sentences on two abundant feature views with a small number of pseudo-labeled ...proposed approach significantly ... See full document
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Automatic Vector Space Based Document Summarization Using Bigrams
... Automatic document summarization is a hot and important research area related with computer science and ...of summarization approaches depending on what the summarization method focuses ... See full document
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