Results 181 to 190 of about 234 (196)

Automatically generating multi-document summarizations

2011 11th International Conference on Intelligent Systems Design and Applications, 2011
This paper describes the News Summarization or NEWSUM algorithm designed to automatically generate multi-document summarizations, hereby focusing on textual documents that concern news items. The NEWSUM algorithm has been implemented and tested in several ways. An overview of both the implementation and the test results are covered in this document.
Daan Van Britsom, Antoon Bronselaer, Guy De Tre   +2 more
openaire   +1 more source

Subtopic-based Multi-documents Summarization

2010 Third International Joint Conference on Computational Science and Optimization, 2010
Multi-documents summarization is an important research area of NLP. Most methods or techniques of multidocument summarization either consider the documents collection as single-topic or treat every sentence as single-topic only, but lack of a systematic analysis of the subtopic semantics hiding inside the documents. This paper presents a Subtopic-based
Shu Gong, Youli Qu, Shengfeng Tian
openaire   +1 more source

Rhetorics-based multi-document summarization

Expert Systems with Applications, 2013
In this paper, a new multi-document summarization framework which combines rhetorical roles and corpus-based semantic analysis is proposed. The approach is able to capture the semantic and rhetorical relationships between sentences so as to combine them to produce coherent summaries.
John Atkinson, Ricardo Munoz
openaire   +1 more source

Event-based Multi-document Summarization

ACM SIGIR Forum, 2016
Daily amount of news reporting real-world events is growing exponentially. At the same time, Organizations are looking for information about current and past events that affects them, such as mergers and acquisitions of companies. The Organizations need to obtain event information in a fast and summarized form to make decisions.
openaire   +1 more source

Aspect based multi-document summarization

2016 International Conference on Computing, Communication and Automation (ICCCA), 2016
Multi-document summarization is useful when a user deals with a group of heterogeneous documents and wants to compile the important information present in the collection, or there is a group of homogeneous documents, taken out from a large corpus as a result of a query.
Deepak Sahoo, Rakesh Balabantaray, Mridumoni Phukon, Saibali Saikia   +3 more
openaire   +1 more source

Subtopic-based multi-document summarization

2009 International Conference on Machine Learning and Cybernetics, 2009
This paper proposes a novel approach for multi-document summarization based on subtopic segmentation. It firstly detects the subtopics in a topic, and then finds the central sentence for each subtopic. The sentences are scored based on their importance in the document and in the subtopic.
null Lin Dai, null Ji-Liang Tang, null Yun-Qing Xia   +2 more
openaire   +1 more source

Context-Based Multi-document Summarization

2018
Automatic text summarization is leading topic of information retrieval research due to increasing online transfer of information. The large volume of information is limited due to constraint of memory devices and access time. The existing summarization system uses the sentence extraction technique where the important sentences are extracted and ...
Sheetal Sonawane, Archana Ghotkar, Sonam Hinge   +2 more
openaire   +1 more source

Multi-document Text Summarization Tool

2020
In today’s world, there is a massive amount of data being continuously generated every minute. This data can be utilised to gain a large amount of information that can have numerous uses. However, it is difficult to obtain this information because of the speed and volume of data being generated.
Richeeka Bathija, Pranav Agarwal, Rakshith Somanna, G. B. Pallavi   +3 more
openaire   +1 more source

Multi-document Summarization using Tensor Decomposition

Computación y Sistemas, 2014
The problem of extractive text summarization for a collection of documents is defined as selecting a small subset of sentences so the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a new model for the problem of extractive summarization, where we strive to obtain a summary that ...
Marina Litvak, Natalia Vanetik
openaire   +1 more source

Automated multi-document summarization in NeATS

Proceedings of the second international conference on Human Language Technology Research -, 2002
This paper describes the multi-document text summarization system NeATS. Using a simple algorithm, NeATS was among the top two performers of the DUC-01 evaluation.
Chin-Yew Lin, Eduard Hovy
openaire   +1 more source