[PDF] Top 20 Extractive Multi-Document Summarization using Neural Network
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Extractive Multi-Document Summarization using Neural Network
... for Multi-record Summarization by Liu Na (2014) [15] considering Titled-LDA figuring which models title and substance of files at that point mixes them by disproportionate ... See full document
6
An Unsupervised Multi Document Summarization Framework Based on Neural Document Model
... in multi-document summarization task, for ...45 document sets respectively. Each document set has 25 news articles for summarization and 4 human-written summaries as ground ... See full document
10
Efficient Multi-Document Summary Generation Using Neural Network
... texts. Summarization systems provide the possibility of searching the important keywords of the texts and so the consumer will expend less time on reading the whole ...of summarization system is to generate ... See full document
6
An Extractive Summarization of Document Using Conceptual Mining and Sentence Ranking
... text document of any four topic (computer network, data mining, machine learning, image processing) is given as input, and the output will be the topic detection of the document to which it belongs ... See full document
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Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi Document Summarization
... Importantly, we argue that predicting sentence similarity within the context of summarization has its uniqueness. It estimates if two sentences con- tain redundant information based on both sur- face word form and ... See full document
12
Graph based Neural Multi Document Summarization
... three using each of the three types of graphs discussed earlier, and one without using any ...each document clus- ter, we tokenize all the documents into sentences and generate a graph representation ... See full document
11
Discourse-Aware Hierarchical Attention Network for Extractive Single-Document Summarization
... RNN-based approaches were introduced to nat- ural language processing tasks by the pioneering work by Bahdanau et al. (2015) and Luong et al. (2015), originally for machine translation. Rush et al. (2015) applied the ... See full document
10
Fast and Robust Compressive Summarization with Dual Decomposition and Multi Task Learning
... for multi-document summarization, using a model that jointly extracts and compresses ...a multi-task learning frame- work to take advantage of existing data for extractive ... See full document
11
Automatic Amharic Text Summarization using NLP Parser
... multiple document Amharic text summarization. Multi-document summarization is the main task in natural language processing and summarizing a huge text document into a short and ... See full document
7
Neural Extractive Text Summarization with Syntactic Compression
... Recent neural network approaches to summa- rization are largely either selection-based ex- traction or generation-based ...a neural model for single-document summarization based on ... See full document
12
A Novel Approach for Document Ranking in Digital Libraries using Extractive Summarization
... Page Content Rank Algorithm: - Jaroslav Pokorny et al.[5] gave a ranking method of page relevance ranking employing Web Content Mining(WCM) technique, called Page Content Rank (PCR). This method combines a number of ... See full document
7
Extractive Techniques for Automatic Document Summarization: A Survey
... for multi-lingual summarization and ...multiple summarization algorithms (at arbitrary compression rates) such as position-based, centroid-based, largest common subsequence, and ...a ... See full document
7
Revisiting the Centroid based Method: A Strong Baseline for Multi Document Summarization
... for extractive document summarization is a simple and fast baseline that ranks sentences based on their similarity to a centroid ...each document prior to constructing the ...for ... See full document
6
Extractive Multi Document Summarization with Integer Linear Programming and Support Vector Regression
... We present a new method to generate extractive multi-document summaries. The method uses Integer Linear Programming to jointly maximize the importance of the sentences it includes in the summary and ... See full document
16
Extractive Summarization Using Multi Task Learning with Document Classification
... The neural network-based approaches rely heavily on large amounts of reference sum- maries for training neural models, and conse- quently, for tuning a large number of ... See full document
10
Video Summarization using Convolutional Neural Network
... video summarization techniques for the multiple egocentric contexts the characteristics of FPV, and how FPV summarization techniques differ from ...video summarization and review and organizes the ... See full document
7
Text Summarization using Neural Network Theory
... a summarization tool for news articles would be extremely useful, since for given news topic or event, there are a large number of available articles from the various news agencies and ...structured ... See full document
7
The Benchmark of Paragraph and Sentence Extraction Summaries on Outlier Document Filtering Applied Multi-Document Summarizer
... outlier document filtering (ODF) for extractive sentence ...systems’ using DUC 2006. Furthermore, we add extractive paragraph summarization to the same ...Although extractive ... See full document
7
Extractive Summarization with SWAP NET: Sentences and Words from Alternating Pointer Networks
... an extractive summary and based on this output, the second step predicts keywords which are used for abstractive ...for extractive summarization and for abstractive summarization they generate ... See full document
10
Study on Multi Document Summarization by Machine Learning Technique for Clustered Documents
... Multi-document summarization methods can be either extractive or ...abstractive summarization attempts to gain an understanding of the main concepts in a document ...hand, ... See full document
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