[PDF] Top 20 Multi Document Summarization Using A* Search and Discriminative Learning
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Multi Document Summarization Using A* Search and Discriminative Learning
... the summarization model. Next in sec- tion 3 we present an A* search algorithm for finding the best scoring (argmax) summary under the model with a constraint on the maximum summary ...performs ... See full document
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An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning
... Natural Language Processing (NLP) is an area of research and application that analyze how computers are used for understanding and manipulating natural language text or speech to achieve the desired tasks. The goal of ... See full document
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Multi Document Summarization using Fuzzy and Hierarchical Approach
... numerous search queries on the search engine on the Internet every ...internet search engines such as Google, Yahoo, Bing and so ...The search engine as a response provides information in ... See full document
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A General Optimization Framework for Multi Document Summarization Using Genetic Algorithms and Swarm Intelligence
... There is only one employed bee per food source (the number of employed bees in the colony is equal to the number of food sources investigated in parallel). Employed bees collect food from their food source and dance in ... See full document
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Fear the REAPER: A System for Automatic Multi Document Summarization with Reinforcement Learning
... reinforcement learning (RL) algorithms are concerned, and the optimal ILP did not outperform ASRL using the same reward func- ...re- search by utilizing an algorithm that intends to improve upon the ... See full document
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Supervised Learning of Automatic Pyramid for Optimization Based Multi Document Summarization
... There are several possible ways how to improve the approximation of AP. First, more semantically- oriented features could be developed, e.g., fea- tures based on propositions rather than sentences or n-grams, or word ... See full document
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Learning to Create Sentence Semantic Relation Graphs for Multi Document Summarization
... Linking facts across documents is a challen- ging task, as the language used to express the same information in a sentence can vary signi- ficantly, which complicates the task of multi- document ... See full document
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Using External Resources and Joint Learning for Bigram Weighting in ILP Based Multi Document Summarization
... ILP summarization framework, but make improvement from three as- ...to using information from the test documents, such as doc- ument frequency, syntactic role in a sentence, ...SentiWordNet. ... See full document
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Extractive Multi-Document Summarization using Neural Network
... machine learning with the organized endeavors among PCs and human ...Single Document Summarization and Multiple Document ...conveyed using single record is called as Single ... See full document
6
Query-Focused Multi-Document Summarization Using Co-Training Based Semi-Supervised Learning
... Abstract. This paper presents a novel approach to query-focused multi-document summarization. As a good biased summary is expected to keep a balance among query relevance, content salience and ... See full document
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Automatically Learning Cognitive Status for Multi Document Summarization of Newswire
... summary using only a common noun reference (these were identified by hand, as common noun coreference cannot be performed re- liably enough by automatic means), indicating that 29% of people mentioned in human ... 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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Using Statistical and Semantic Models for Multi-Document Summarization
... benchmarks. Learning pre-trained vectors used in seman- tic models further, on given corpus, can give addition spike in ...performance. Using weighing techniques in between various statistical models too ... See full document
15
Study on Multi Document Summarization by Machine Learning Technique for Clustered Documents
... generate discriminative and semantic rich representations for topics and documents so that the most representative and non-redundant sentences can be selected to form a succinct and informative ...of ... See full document
5
Extractive Summarization Using Multi Task Learning with Document Classification
... a document as a baseline. We also built a base- line classifier LREG using logistic regression and human engineered ...the document, number of entities, nouns, verbs, adverbs, and adjectives in the ... See full document
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Scalable Multi-document Summarization Using Natural Language Processing
... several summarization methods have been proposed by ...Luhn using term frequencies and word collections from The Automatic Creation of Literature Abstracts ...[6] using term frequencies and ... See full document
58
Using AdaBoost Meta Learning Algorithm for Medical News Multi Document Summarization
... weak learning algorithm on various distributions over the training data, and then combining the classifiers produced by the weak learner into a single composite ...to learning problems having either of the ... See full document
9
Multi document summarization using distortion rate ratio
... the vertices on the lower boundary of the convex hull. ∆D and ∆R indicate the amount of distor- tion increase and rate decrease when branch sub- tree S is pruned off. It can be shown that a step on the lower boundary can ... See full document
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Hierarchical Summarization: Scaling Up Multi Document Summarization
... Document Threads: A related track of research investigates discovering threads of documents. While we aim to summarize collections of infor- mation, this track seeks to identify relationships between documents. ... See full document
11
Using Syntactic and Shallow Semantic Kernels to Improve Multi Modality Manifold Ranking for Topic Focused Multi Document Summarization
... focused multi-document ...based summarization method that makes uni- form use of the sentence-to-sentence relation- ships and the sentence-to-topic relationships in a manifold-ranking process (Wan et ... See full document
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