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A Newly Proposed Technique for Summarizing the Abstractive Newspapers' Articles based on Deep Learning

Sherif Kamel Hussein
2020 Zenodo  
It is very difficult for human beings to manually extract the summary of large documents of text.  ...  More specific, Abstractive Text Summarization (ATS), is the task of constructing summary sentences by merging facts from different source sentences and condensing them into a shorter representation while  ...  Original Text Word segmentation Phrase combination Coreference resolution Morphological reduction Phrase acquisition Phrase refinement Processed text Phrase sequence Text summary  ... 
doi:10.5281/zenodo.4420866 fatcat:xqgwahkeinbjfhfeglsmrc3dra

Page 523 of Computational Linguistics Vol. 28, Issue 4 [page]

2002 Computational Linguistics  
INSPEC database for physics, electronics and computing. http: / /www.iee.org.uk/publish/inspec / Jing, Hongyan. 2000. Sentence reduction for automatic text summarization.  ...  Processing Manual: Rules and Guidelines for the Acquisition, Selection, and Technical Processing of Documents and Journal Articles by the Various Components of the ERIC Network. ERIC.  ... 

Developing a Computer Assisted Summary Writing Learning Model

Chew Chiou Sheng, Artificial Intelligence, University of Malaya, Kuala Lumpur, Malaysia, Norisma Idris, David Loh Er Fu, Mimihayu Md Yusof, Wan Effa Jaapar
2018 International Journal of Learning and Teaching  
 Abstract-Summary writing is a process of producing a more concise text through the process of selecting important information and deleting supporting and explanatory details from the source text.  ...  From a study conducted on Malaysian undergraduate students, it was found that majority of them were unable to write a good summary due to lack of prior knowledge and functional knowledge of summarizing  ...  Previous works on summary writing focus on the quality of written summaries, neglecting the comprehension stage before summarizing a text.  ... 
doi:10.18178/ijlt.4.2.94-101 fatcat:7kz75dvvdjfbdaim7hfto2hlty

An Overview of Text Summarization

Laxmi B., P. Venkata
2017 International Journal of Computer Applications  
Automatic text summarization system produces a summary, i.e. short length text that includes all the significant information for the article.  ...  As the vast amount of information is available for every theme on Internet, shortening the information in the form of summary would immensely benefit readers.  ...  The reduction can significantly improve the conciseness of automatic summaries.  ... 
doi:10.5120/ijca2017915109 fatcat:hlpvgrzpd5hord5bfy4zndqexi

Specifics of Development of the Integral Method of Knowledge Estimation

Viktoriya Nikolaevna Golovachyova, Nella Fuatovna Abayeva, Mahabbat Meyramovna Kokkoz, Lezzetzhan Muhamedzhanovna Mustafina, Bakhytzhan Muhamedzhanovna Mustafina
2015 Review of European Studies  
results in reduction of the simulating effect of pedagogical grades on the cognitive activity of students and educational process quality in general.  ...  Besides, physical acquisition of training material is always possible.  ...  Series of various rules for evaluation of grammar quality of the text answer in general may be an estimation criterion γ.  ... 
doi:10.5539/res.v7n7p284 fatcat:36mptx37fvdzjbdvxglgrdzjnm

Automatic Construction of Machine Translation Knowledge Using Translation Literalness
直訳性を利用した機械翻訳知識の自動構築

KENJI IMAMURA, EIICHIRO SUMITA, YUJI MATSUMOTO
2004 Journal of Natural Language Processing  
The effects are evaluated by the MT quality, and about 4.9% of MT results were improved by the latter method.  ...  These rules increase ambiguity or cause incorrect MT results. To overcome this problem, we constrain the sentences used for knowledge extraction to "the appropriate bilingual sentences for the MT."  ...  Acknowledgment The research reported here is supported in part by a contract with the Telecommunications Advancement Organization of Japan entitled, "A study of speech dialogue translation technology based  ... 
doi:10.5715/jnlp.11.2_85 fatcat:ko5jtf73evfdzg4ez4jyrtse4e

The decomposition of human-written summary sentences

Hongyan Jing, Kathleen R. McKeown
1999 Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '99  
Solving the decomposition problem can potentially lead to the automatic acquisition of large corpora for summarization. It also sheds light on the generation of summary text by cutting and pasting.  ...  We define the problem of decomposing human-written summary sentences and propose a novel Hidden Markov Model solution to the problem.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1145/312624.312666 dblp:conf/sigir/JingM99 fatcat:ioavoba5ijgvvc5ypbmbxupeie

Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text Summarization [article]

Juan-Manuel Torres-Moreno
2012 arXiv   pre-print
The results show that Ultra-stemming not only preserve the content of summaries produced by this representation, but often the performances of the systems can be dramatically improved.  ...  However, even using normalization on large texts, the curse of dimensionality can disturb the performance of summarizers.  ...  Summarization using the Ultra-stemming representation for sentence scoring, improve the identification of most relevant sentences from documents.  ... 
arXiv:1209.3126v1 fatcat:6lfhnylxdvatlkfimxp2kkmrcu

Generating Indicative-Informative Summaries with SumUM

Horacio Saggion, Guy Lapalme
2002 Computational Linguistics  
Even though some approaches to text summarization produce acceptable summaries for specific tasks, it is generally agreed that the problem of coherent selection and expression of information in text summarization  ...  Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries.  ...  We thank also Elliott Macklovitch and Diana Maynard, who helped us improve the quality of our article, and the members of the Laboratoire de Recherche Appliquée en Linguistique Informatique (RALI) for  ... 
doi:10.1162/089120102762671963 fatcat:ziupshyti5ebhedftovomzz4cm

Automatic Summarization

Ani Nenkova
2011 Foundations and Trends in Information Retrieval  
It then feeds the set of training examples to (3) a learning algorithm that learns the classification rules for determining whether or not a sentence should be part of the summary.  ...  Summary type Length reduction Time reduction Accuracy loss User-focused 77% 50% 5% Generic 90% 60% 0% Mitre Corp. November 2000  ...  His research focus is on the intersection of text understanding and information systems and includes text summarization, intelligent text retrieval, acquisition of knowledge from texts, and text mining  ... 
doi:10.1561/1500000015 fatcat:gfli2ecy55a2dkwleu5b522au4

Automatic Summarization [chapter]

Lamia Hadrich Belguith, Mariem Ellouze, Mohamed Hedi Maaloul, Maher Jaoua, Fatma Kallel Jaoua, Philippe Blache
2014 Natural Language Processing of Semitic Languages  
It then feeds the set of training examples to (3) a learning algorithm that learns the classification rules for determining whether or not a sentence should be part of the summary.  ...  Summary type Length reduction Time reduction Accuracy loss User-focused 77% 50% 5% Generic 90% 60% 0% Mitre Corp. November 2000  ...  His research focus is on the intersection of text understanding and information systems and includes text summarization, intelligent text retrieval, acquisition of knowledge from texts, and text mining  ... 
doi:10.1007/978-3-642-45358-8_12 dblp:series/tanlp/BelguithEMJJB14 fatcat:zxihwcr2azdjlnio53cgrqk6hy

The challenges of automatic summarization

U. Hahn, I. Mani
2000 Computer  
It then feeds the set of training examples to (3) a learning algorithm that learns the classification rules for determining whether or not a sentence should be part of the summary.  ...  Summary type Length reduction Time reduction Accuracy loss User-focused 77% 50% 5% Generic 90% 60% 0% Mitre Corp. November 2000  ...  His research focus is on the intersection of text understanding and information systems and includes text summarization, intelligent text retrieval, acquisition of knowledge from texts, and text mining  ... 
doi:10.1109/2.881692 fatcat:tddpln5jsrfhdplkbpf64yqvhu

TEG—a hybrid approach to information extraction

Ronen Feldman, Benjamin Rosenfeld, Moshe Fresko
2005 Knowledge and Information Systems  
We also demonstrate the robustness of our system under conditions of poor training-data quality.  ...  The model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labour by relying on statistics drawn from a training corpus  ...  This shows the ability of TEG to effectively ignore bad or inconsistent examples. And it shows the possibility of using TEG to improve the annotation quality.  ... 
doi:10.1007/s10115-005-0204-y fatcat:3ouotughtrbqpilvvbbwhstmxy

Text-Mining: Application Development Challenges [chapter]

Sundar Varadarajan, Kas Kasravi, Ronen Feldman
2003 Applications and Innovations in Intelligent Systems X  
Special emphasis is placed on post-information extraction processing, such as improving the relevance of the extracted information, summarization models, techniques for handling typographical errors, resolution  ...  First, project management issues are discussed, including a process for capturing business requirements and mapping them into features and linguistic patterns, development of linguistic rules, rule development  ...  Reduction: This form of summary reduces the size of an article to a specific size or percentage of the original document's length.  ... 
doi:10.1007/978-1-4471-0649-4_17 fatcat:ruq2vvv5xzbxtp5xl3bpuncjr4

BRIEF BIOGRAPHICAL NOTES

1952 Educational review (Birmingham)  
Originality/value -Several key components are integrated for web site summarization for the first time, including feature selection and link analysis, key phrase and key sentence extraction.  ...  Abstract: Purpose -Summarization of an entire Web site with diverse content may lead to a summary heavily biased towards the site's dominant topics.  ...  We are very thankful to the authors of the X-means clustering algorithm for making their software available. The anonymous reviewers provided several constructive suggestions.  ... 
doi:10.1080/0013191520040207 fatcat:lkqhyelrjndfdphmigjurvf24q
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