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User-Focused Multi-Document Summarization with Paragraph Clustering and Sentence-Type Filtering

Yohei Seki, Koji Eguchi, Noriko Kando
2004 NTCIR Conference on Evaluation of Information Access Technologies  
We compare several document clustering techniques for multi-document summarization in the NTCIR-4 TSC test collection.  ...  From the results, we draw conclusions regarding the nature of the multi-document summarization with respect to redundancy reduction strategies.  ...  Algorithm 1 Our Clustering-based Multi-document Summarization Paragraph Clustering Stage Source documents were segmented to paragraph units, then features with term frequencies were computed for each  ... 
dblp:conf/ntcir/SekiEK04 fatcat:mv4zefjeszcjbnddzspsm34vhe

Development and Evaluation of a Multi-document Summarization Method Focusing on Research Concepts and Their Research Relationships [chapter]

Shiyan Ou, Christopher S. G. Khoo, Dion H. Goh
2005 Lecture Notes in Computer Science  
in a Web-based interface to generate a multi-document summary.  ...  The summarization method was evaluated in a user study to assess the quality and usefulness of the generated summaries in comparison to a sentence extraction method used in MEAD and a method that extracts  ...  With sentence extraction, documents or sentences across all the documents are clustered, following which, a small number of sentences are selected from each cluster and concatenated into a summary [1,  ... 
doi:10.1007/11599517_32 fatcat:si3zzhovyzbovfj6fqve73ivfm

A New Model for Arabic Multi-Document Text Summarization

Khulood Abu Maria, Khalid Mohammad Jaber, Mossab Nabil Ibrahim
2018 International Journal of Innovative Computing, Information and Control  
Therefore, the rise of the desire for Arabic multi documents text summarization (at the instant rates possible, coherent, grammatical and meaningful sentences) is increased.  ...  This model of Arabic text summarization could effectively and rapidly summarize Arabic multi-documents in real time.  ...  The general differences between text summarization systems can be categorized by the kind of input document (Single, Multi-Document as shown in Figure 1 ), summarization types (Generic, User or Topic  ... 
doi:10.24507/ijicic.14.04.1443 fatcat:rfrstusxwjg5bnsmyntz7is7by

Automatic multidocument summarization of research abstracts: Design and user evaluation

Shiyan Ou, Christopher S.G. Khoo, Dion H. Goh
2007 Journal of the American Society for Information Science and Technology  
Two types of variable-based summaries generated using the summarization method -with or without the use of a taxonomy -were compared against a sentence-based summary that only lists the research objective  ...  The purpose of this study was to develop a method for automatic construction of multi-document summaries of sets of research abstracts that may be retrieved by a digital library or search engine in response  ...  Multi-document summarization mainly focuses on the similarities and differences across documents.  ... 
doi:10.1002/asi.20618 fatcat:fg5c2sneijd4rmo4ybsxjdsufm

A Survey of Text Summarization Extractive Techniques

Vishal Gupta, Gurpreet Singh Lehal
2010 Journal of Emerging Technologies in Web Intelligence  
An extractive summarization method consists of selecting important sentences, paragraphs etc. from the original document and concatenating them into shorter form.  ...  It is very difficult for human beings to manually summarize large documents of text. Text Summarization methods can be classified into extractive and abstractive summarization.  ...  Hub/Authority [39] framework is multi document summarization system which, firstly detect the sub-topics in multi-documents by sentence clustering and extract the feature words (or phrase) of different  ... 
doi:10.4304/jetwi.2.3.258-268 fatcat:anms2x4aczftdnedejeo2tznwm

An Overview on Document Summarization Techniques

Archana AB, Sunitha C
2020 International journal of recent advances in engineering & technology  
Query-focused summaries enable users to find more relevant documents more accurately, with less need to consult the full text of the document.  ...  Since digitally stored information is more and more available, users need suitable tools able to select, filter, and extract only relevant information.  ...  Multi-document summary -Single document summary provide the most relevant information contained in single document to the user that helps the user in deciding whether the document is related to the topic  ... 
doi:10.46564/ijraet.2020.v08i03.007 fatcat:liyqzcmehncb5lxfkxoqfil4my

Tweet Contextualization (Answering Tweet Question) - the Role of Multi-document Summarization

Pinaki Bhaskar, Somnath Banerjee, Sivaji Bandyopadhyay
2013 Conference and Labs of the Evaluation Forum  
The Offline multi-document summarization system is based on document graph, clustering and sentence compression. In the Focused IR system, Wikipedia documents are indexed using Lucene with NE field.  ...  In our system there are three major sub-systems; i) Offline multi-document summarization, ii) Focused IR and iii) online multi-document Summarization.  ...  We acknowledge the support of the Department of Electronics and Information Technology (DeitY), Ministry of Communications & Information Technology (MCIT), Government of India funded project "Development  ... 
dblp:conf/clef/BhaskarBB13 fatcat:bdhrsixvhjft3jcitffjjad2f4

The Smart/Empire TIPSTER IR system

Chris Buckley, Janet Walz, Claire Cardie, Scott Mardis, Mandar Mitra, David Pierce, Kiri Wagstaff
1996 Proceedings of a workshop on held at Baltimore, Maryland October 13-15, 1998 -  
This suggests that work on coreference becomes particularly crucial when working with sentence based summaries. Multi-Document Summarization.  ...  Three are briefly described below: Boolean filters, clusters, and phrases. Automatic Boolean Filters Smart expands user queries by adding terms occurring in the top documents.  ... 
doi:10.3115/1119089.1119111 dblp:conf/tipster/BuckleyWCMMPW98 fatcat:d5kxetucnbad7axxiqqoly5kbu

Sentence Selection Using Latent Semantic Analysis for Automatic Question Generation in E-Learning System

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
For the Teaching-Learning process, both the learners and teachers are highly preferred the online system i.e, E-Learning because of its user-friendly approach such as learning at anytime and anywhere.  ...  We have proposed the computer-assisted system to summarize the learning content of the material using Machine Learning techniques.  ...  In the end, multi-document summarization elaborates the two user studies that test the models of multi-document summarization.  ... 
doi:10.35940/ijitee.i7492.078919 fatcat:zhn6jf2t7ngz3jwvya3t43mucu

Summarization from medical documents: a survey

Stergos Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos
2005 Artificial Intelligence in Medicine  
types of summarization techniques.  ...  It mainly focuses on the issue of scaling to large collections of documents in various languages and from different media, on personalization issues, on portability to new sub-domains, and on the integration  ...  Spyropoulos and Dr. George Paliouras, for their helpful and constructive comments. Many thanks also to Ms. Eleni Kapelou and Ms. Irene Doura for checking the use of English.  ... 
doi:10.1016/j.artmed.2004.07.017 pmid:15811783 fatcat:n7u6ji5t2rgkvjktacjf4rdire

Customization in a unified framework for summarizing medical literature

N. Elhadad, M.-Y. Kan, J.L. Klavans, K.R. McKeown
2005 Artificial Intelligence in Medicine  
Methods and Material: Our summarizer employs a unified user model to create a tailored summary of relevant documents for either a physician or lay person.  ...  Results: The resulting summaries combine both machine-generated text and extracted text that comes from multiple input documents.  ...  Both summarizers perform multi-document automatic summarization, using categorization, information extraction, and language generation to cull specific facts and passages which can help the user determine  ... 
doi:10.1016/j.artmed.2004.07.018 pmid:15811784 fatcat:xsykbwtsynf55bzlc4jrt6afbe

Automated Classroom Lecture Note Generation Using Natural Language Processing and Image Processing Techniques

Sandanayake T.C., University of Moratuwa, Katubedda, Sri Lanka,
2019 International Journal of Advanced Trends in Computer Science and Engineering  
The study has adapted Natural Language Processing and Image Processing techniques. Main components of the research were text segmentation, text summarization, topic modeling, and diagram recognition.  ...  These different methods can be use of power point, white board drawings, and online learning platforms, audio and video inputs.  ...  There are two main types of text summarization methods, as extractive text summarization and abstractive text summarization [6, 7] .  ... 
doi:10.30534/ijatcse/2019/16852019 fatcat:w24qujpsqrhc7pof7wpdk2t76u

A Hybrid Tweet Contextualization System using IR and Summarization

Pinaki Bhaskar, Somnath Banerjee, Sivaji Bandyopadhyay
2012 Conference and Labs of the Evaluation Forum  
The INEX TC task has two main sub tasks, Focused IR and Automatic Summarization. In the Focused IR system, we first preprocess the Wikipedia documents and then index them using Nutch with NE field.  ...  The automatic summarization system takes as input the query tweet along with the title from the most relevant text document.  ...  We acknowledge the support of the IFCPAR funded Indo-French project "An Advanced Platform for Question Answering Systems" and the DIT, Government of India funded project "Development of Cross Lingual Information  ... 
dblp:conf/clef/BhaskarBB12 fatcat:d7sbdp2v6jedbil4iohgenpjmm

Text Summarization in the Biomedical Domain [article]

Milad Moradi, Nasser Ghadiri
2019 arXiv   pre-print
Different types of challenges are introduced, and methods are discussed concerning the type of challenge that they address.  ...  Biomedical literature summarization is explored as a leading trend in the field, and some future lines of work are pointed out.  ...  Methods fall into different categories of abstractive, extractive, single-document, multi-document, generic, and user-oriented.  ... 
arXiv:1908.02285v1 fatcat:l24yebd6hbag5isryfj27zhtk4

An Overview of Text Summarization

Laxmi B., P. Venkata
2017 International Journal of Computer Applications  
This paper presents a comprehensive survey of contemporary text summarization of extractive and abstractive approaches.  ...  Hence, the natural language processing research community is developing new methods for summarizing the text mechanically.  ...  Depending on the type user the summary can be catagorized as User-focused summaries (or Topic focused or query focused) and generic summaries.  ... 
doi:10.5120/ijca2017915109 fatcat:hlpvgrzpd5hord5bfy4zndqexi
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