[PDF] Top 20 A Subjective Logic Framework for Multi Document Summarization
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A Subjective Logic Framework for Multi Document Summarization
... Effect of Context Adjustment: Tables 1 and 2 have included the ROUGE evaluation scores for SubSum_NoAdj and CF_NoAdj as two other comparison partners of SubSum and CF. SubSum_NoAdj and CF_NoAdj are the modified versions ... See full document
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A Sentence Compression Based Framework to Query Focused Multi Document Summarization
... compression-based framework for query-specific ...the summarization models on the standard Document Understanding Confer- ence (DUC) 2006 and 2007 corpora 2 for ... See full document
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Deconstructing Human Literature Reviews – A Framework for Multi Document Summarization
... the framework, the objective was to compare its “human-ness” represented by its Comprehensibility, Readability and Usefulness against human-written literature reviews and machine-generated sentence ...the ... See full document
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Towards Abstractive Multi Document Summarization Using Submodular Function Based Framework, Sentence Compression and Merging
... In this paper, we divide the whole task of sum- marization in two main phases: document shrink- ing and summarization. In the first phase, we ap- ply sentence compression and merging to produce concise and ... See full document
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Study on Multi Document Summarization by Machine Learning Technique for Clustered Documents
... Given a set of topically related documents, the segmentation process is carried out using a Bayesian framework. By using similar sentences from different documents more accurate segment likelihood estimations are ... See full document
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Automatic Text Document Summarization
... the document first and scoring the individual sentences with respect to the ...in document summarization to discover the topics present in a document ...clustering-based summarization ... See full document
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Topic-Sensitive Multi-document Summarization Algorithm
... for multi-document summarization based on topic model has been ...for summarization in 2009. This model made use of both the term-document and term- sentence associations to help the ... See full document
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Multi Document Summarization Using K Medoids Clustering Approach
... Abstract: Multi document summarization is the process of transforming a set of documents into a single summarized ...summarized document can give overall idea of the document ... See full document
5
Adapting the Neural Encoder Decoder Framework from Single to Multi Document Summarization
... from multi-document ...single- document inputs with a strong extractive summa- rization algorithm (MMR for Maximal Marginal Relevance; Carbonell and Goldstein, 1998) that identifies important source ... See full document
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Content Selection in Multi-Document Summarization
... DPP: Determinantal point processes (DPPs) (Kulesza and Taskar, 2012) are prob- abilistic models of sets which balance the selection of important information and diverse groups of sentences within a given length. ... See full document
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Multi Document Summarization of Evaluative Text
... in summarization, we chose to develop our own sentence extractor as a first attempt at summarizing evaluative argu- ...open-source framework for multi- document summarization, to suit ... See full document
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Subtopic driven Multi Document Summarization
... Note that we use u to represent the vector dimen- sion throughout the model description (specific value settings are given in Section 5). The rep- resentations for news sentences S and news docu- ments D are learned in a ... See full document
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System Combination for Multi document Summarization
... We present a novel framework of system combination for multi-document summarization. For each input set (input), we generate candidate summaries by combining whole sentences from the summaries ... See full document
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A General Optimization Framework for Multi Document Summarization Using Genetic Algorithms and Swarm Intelligence
... extractive multi-document ...optimization framework where any function of input documents and a system summary can be plugged ...Our framework includes two kinds of sum- marizers – one based ... See full document
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A Supervised Aggregation Framework for Multi Document Summarization
... extractive summarization by learning to summarize documents auto- ...treats summarization task as a sequence labeling problem (Shen et ...in summarization (Svore et ... See full document
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An Unsupervised Multi Document Summarization Framework Based on Neural Document Model
... exploding, multi-document summarization is attracting particular atten- tion for the ability to help people get the main ideas in a short ...the document set as a group of sentences while ... See full document
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Towards Coherent Multi Document Summarization
... A multi-document extension of RST is Cross-document Structure Theory (CST), which has been applied to MDS (Zhang et ...of summarization based on lightweight ... See full document
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Multi document Summarization Using Bipartite Graphs
... In the summarization task, optimization of the three properties discussed in Section 1, relevance, non-redundancy and readability, is required. This is a global inference problem, which can be solved by two ... See full document
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An Exploration of Document Impact on Graph Based Multi Document Summarization
... proposed document-based graph model (de- noted as DGM) with different settings is compared with the basic graph-based Model (denoted as GM), the top three performing systems and two baseline systems on DUC2001 and ... See full document
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From Single to Multi document Summarization
... Each sentence in the document set is then ranked, using the key concept structures. An example is shown in Figure 2. The ranking algorithm rewards most specific concepts first; for example, a sentence containing ... See full document
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