[PDF] Top 20 Toward Abstractive Summarization Using Semantic Representations
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Toward Abstractive Summarization Using Semantic Representations
... novel abstractive summarization framework that draws on the recent develop- ment of a treebank for the Abstract Meaning Representation ...source semantic graph into a summary graph, mak- ing use of ... See full document
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Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization
... Distributional Semantic Reward During eval- uating the quality of the generated sentences, R OUGE looks for exact matches between refer- ences and generations, which naturally overlooks the expression diversity of ... See full document
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A Semantic Based Approach for Abstractive Multi-Document Text Summarization
... domain. Abstractive summarization will serve as a tool for generating summary which is semantically correct and produced fewer amounts of sentences in ...Extractive summarization leads to sentence ... See full document
10
Abstractive News Summarization based on Event Semantic Link Network
... Different abstractive summarization methods can be summarized into four technique routes: (1) sentence fusion based methods (Barzilay and McKeown, 2005; Filippova and Strube, 2008; Banerjee et ...Basic ... See full document
11
Framework for Abstractive Summarization using Text to Text Generation
... tive summarization in (Rusu et ...call semantic graphs, derived from triplets, and then using said graphs to identify the most interesting sentences for the ... See full document
10
Survey Paper on Text Summarization Methods
... Abstractive Summarization works by generating a sentence from data having semantic representation and after that generate a summary by using natural language processing (NLP) ...version. ... See full document
6
Controlling Length in Abstractive Summarization Using a Convolutional Neural Network
... Convolutional neural networks (CNNs) have met great success in abstractive summariza- tion, but they cannot effectively generate sum- maries of desired lengths. Because generated summaries are used in difference ... See full document
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Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization
... Most of the current abstractive text sum- marization models are based on the sequence-to-sequence model (Seq2Seq). The source content of social media is long and noisy, so it is difficult for Seq2Seq to learn an ... See full document
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Abstractive Text Summarization Based on Deep Learning and Semantic Content Generalization
... novel abstractive TS technique that combines deep learning models of encoder-decoder architecture and semantic-based data ...in abstractive TS focuses in either of the aforementioned parts, the ... See full document
11
Abstractive Text Summarization using Sequence to sequence RNNs and Beyond
... document, around which the story revolves. In order to accomplish this goal, we may need to go beyond the word-embeddings-based represen- tation of the input document and capture addi- tional linguistic features such as ... See full document
11
A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
... Extractive summarization. K˚ageb¨ack et al. (2014) and Yin and Pei (2015) use neural networks to map sentences into vectors and select sentences based on those vectors. Cheng and Lapata (2016), Nallapati et al. ... See full document
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A New Method of Text Categorization and Summarization with Fuzzy Confusion Matrix
... Text Summarization achieves the task of compression of the text size while preserving the overall ...Text summarization can be classified as extrinsic or extractive summarization and intrinsic or ... See full document
8
Global Encoding for Abstractive Summarization
... for abstractive summarization can suffer from repetition and semantic irrelevance, causing grammatical errors and insufficient reflection of the main idea of the source ... See full document
7
SSAS: Semantic Similarity for Abstractive Summarization
... In this work, we proposed a novel metric SSAS for semantic assessment of abstractive summaries. Our experiments show that SSAS outperforms previously proposed metrics. While the metric shows a very strong ... See full document
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Unsupervised Semantic Abstractive Summarization
... On the other hand, most Abstractive methods take advantages of the recent developments in deep learning. Specifically, the recent success of the sequence to sequence Sutskever et al. (2014) learning models, where ... See full document
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PERFORMANCE OF SEPARATED RANDOM USER SCHEDULING (SRUS) AND JOUNT USER SCHEDULING (JUS) IN THE LONG TERM EVOLUTION ADVANCED
... Text summarization is the process of extracting salient information from the source text and to present that information to the user in the form of ...Automatic abstractive summarization provides the ... See full document
9
Multimodal Abstractive Summarization for How2 Videos
... study abstractive summariza- tion for open-domain ...news summarization, the goal is less to “compress” text information but rather to provide a fluent textual summary of infor- mation that has been ... See full document
10
Abstractive Multi document Summarization with Semantic Information Extraction
... generate abstractive summary based on Abstract Meaning Represen- tation (AMR) (Liu et ...BSUs semantic link ...recent abstractive summarization meth- od generates new sentences by selecting ... See full document
6
Abstractive Meeting Summarization with Entailment and Fusion
... meeting summarization, and propose a novel framework to generate summaries composed of grammatical ...generate abstractive summary ...disregard semantic information, we integrate se- mantics by means ... See full document
11
Study on Multi Document Summarization by Machine Learning Technique for Clustered Documents
... 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 ... See full document
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