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Automatic Texts Summarization: Current State of the Art

Nabil ALAMI, Mohammed MEKNASSI, Noureddine RAIS
2015 Journal of Asian Scientific Research  
This study is one of very few studies which have investigated on automatic text summarization field.  ...  In this paper we expose a literature review of recent techniques and works on automatic text summarization field research, and then we focus our discussion on some works concerning automatic text summarization  ...  The quality of an automatic summarization based on keywords will be enhanced if these keywords are known in advance.  ... 
doi:10.18488/journal.2/2015.5.1/2.1.1.15 fatcat:kjq3xaofczchvdgajfcmff6q7u

Automatic Keyword Extraction for Text Summarization: A Survey [article]

Santosh Kumar Bharti, Korra Sathya Babu
2017 arXiv   pre-print
In this paper, recent literature on automatic keyword extraction and text summarization are presented since text summarization process is highly depend on keyword extraction.  ...  Text summarization is emerged as an important research area in recent past. In this regard, review of existing work on text summarization process is useful for carrying out further research.  ...  Section 2 presents a review on automatic keyword extraction Section 3 presents a review on text summarization process. A review on automatic text summarization methologies are given in Section 4.  ... 
arXiv:1704.03242v1 fatcat:poa2yh2uhbcgfaemgfqa5ylxim

KEYWORD DISTINGUISHING METHODS IN THE PROCESS OF SCIENTIFIC TEXTS RENDERING
МЕТОДЫ ВЫДЕЛЕНИЯ КЛЮЧЕВЫХ СЛОВ ПРИ РЕФЕРИРОВАНИИ НАУЧНОГО ТЕКСТА

T. N. Moskvitina, South Ural State Humanitarian Pedagogical University
2018 Vestnik Tomskogo Gosudarstvennogo Pedagogičeskogo Universiteta  
Automatic Keyword Extraction On the premise of past work done towards automatic keyword extraction from the text for its summarization, extraction systems can be classified into four classes, namely, simple  ...  The keywords for the article under consideration are determined based on these scores and are used to summarize the article.  ...  Summarization Process Based on the literature, text summarization process can be characterized into five types, namely, based on the number of the document, based on summary usage, based on techniques  ... 
doi:10.23951/1609-624x-2018-8-45-50 fatcat:zyhcnwwkprdl7akq4tu2hgz2we

Automatic patent document summarization for collaborative knowledge systems and services

Amy J.C. Trappey, Charles V. Trappey, Chun-Yi Wu
2009 Journal of Systems Science and Systems Engineering  
In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach.  ...  The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a  ...  Yeh et al. (2005) provide a modified corpus based approach and latent semantic analysis based on text relationship maps for automatic text summarization.  ... 
doi:10.1007/s11518-009-5100-7 fatcat:q7ij663kcnh6fp2iq5tcod2fvy

TIARA

Furu Wei, Shixia Liu, Yangqiu Song, Shimei Pan, Michelle X. Zhou, Weihong Qian, Lei Shi, Li Tan, Qiang Zhang
2010 Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '10  
To help users understand the topic-based summarization results, TIARA employs several interactive text visualization techniques to explain the summarization results and seamlessly link such results to  ...  In addition to extracting topics, TIARA derives time-sensitive keywords to depict the content evolution of each topic over time.  ...  We would like to thank Xiaoxiao Lian, Xiaohua Sun, and Kevin Brown for their work on the TIARA UI design.  ... 
doi:10.1145/1835804.1835827 dblp:conf/kdd/WeiLSPZQSTZ10 fatcat:ahtbbaqv6ffg7kj46ob7prt3uq

Text Summarization Extraction System (TSES) Using Extracted Keywords

Rafeeq Al-Hashemi
2010 ˜The œinternational Arab journal of e-technology  
Each sentence ranked depending on many features such as the existence of the keywords/keyphrase in it, the relation between the sentence and the title by using a similarity measurement and other many features  ...  The system uses the extracted keywords/keyphrases to select the important sentence.  ...  Related Work The study of text summarization [3] proposed an automatic summarization method combining conventional sentence extraction and trainable classifier based on Support Vector Machine.  ... 
dblp:journals/iajet/Al-Hashemi10 fatcat:nwzqb6nmkrdg7nqpvbe466tcii

deepMINE - Natural Language Processing based Automatic Literature Mining and Research Summarization for Early Stage Comprehension in Pandemic Situations specifically for COVID-19 [article]

Bhrugesh Pravinchandra Joshi, Vishvajit D Bakrola, Parth Shah, Ramar Krishnamurthy
2020 bioRxiv   pre-print
We have developed a complete automatic literature mining system that delivers efficient and fast mining from existing biomedical literature databases.  ...  The system is currently scanning nearly 1,46,115,136 English words from 29,315 research articles in not greater than 1.5 seconds with multiple search keywords.  ...  To overcome this limitation we developed a research text summarizer that can generate a technical summary by scanning all the research articles derived from user-entered keyword(s).  ... 
doi:10.1101/2020.03.30.014555 fatcat:m4vbzui7ibfy3cvepczsxrf7sy

Noun retrieval effect on text summarization and delivery of personalized news articles to the user's desktop

Christos Bouras, Vassilis Tsogkas
2010 Data & Knowledge Engineering  
In this article, we present the keyword extraction techniques, exploring the effects that part of speech tagging has on the summarization procedure of an existing system.  ...  Text summarization and categorization, as well as personalization of the results, have always been some of the most demanding information retrieval tasks.  ...  Based on the fact that many information retrieval (IR) tasks, such as classification, summarization or clustering rely heavily on keyword -oriented information originating from the source texts, it is  ... 
doi:10.1016/j.datak.2010.02.005 fatcat:lqcrak3ourhixlc7yf2oaubqtq

PeRSSonal's core functionality evaluation: Enhancing text labeling through personalized summaries

Christos Bouras, Vassilis Poulopoulos, Vassilis Tsogkas
2008 Data & Knowledge Engineering  
We focalize to the core of the mechanism and more specifically, we present the algorithms used for the summarization and the categorization of texts.  ...  Before presenting the information back to the end user, the core of our mechanism automatically categorizes data and then extracts personalized summaries.  ...  Related work The procedure of creating efficient, automatic text summaries begins from the late 1950s with the analytic approach from Luhn [13] , whose classic work is based on analysis of words and sentences  ... 
doi:10.1016/j.datak.2007.07.007 fatcat:qg3nfbg2rveqpgx3s7wz77nu3i

Toward Selectivity Based Keyword Extraction for Croatian News [article]

Slobodan Beliga, Ana Meštrović, Sanda Martinčić-Ipšić
2014 arXiv   pre-print
Preliminary report on network based keyword extraction for Croatian is an unsupervised method for keyword extraction from the complex network.  ...  Selectivity based extraction does not require linguistic knowledge while it is purely derived from statistical and structural information en-compassed in the source text which is reflected into the structure  ...  TextRank is derived from PageRank and introduced to graph based text processing, keyword and sentence extraction.  ... 
arXiv:1407.4723v1 fatcat:5agto5tpmfadpc53p6hhgq3o34

Knowledge-guided Unsupervised Rhetorical Parsing for Text Summarization [article]

Shengluan Hou, Ruqian Lu
2019 arXiv   pre-print
The subroutine-based summarization model purely depends on the derived rhetorical structure trees and can generate content-balanced results.  ...  for text summarization.  ...  Subroutine-based Model for Automatic Text Summarization In this section, we present a subroutine-based model for automatic text summarization, which has been introduce in our previous paper [37] .  ... 
arXiv:1910.05915v1 fatcat:fbylzfirhzdvjosixhcxpmvoyq

An R&D knowledge management method for patent document summarization

Amy J.C. Trappey, Charles V. Trappey
2008 Industrial management & data systems  
The approach relies on a powerful text-mining engine as the pre-process module for key phrase extraction.  ...  Significant information density is defined based on the domain-specific key concepts/phrases, relevant phrases, title phrases, indicator phrases and topic sentences of a given patent document.  ...  Kao's technical support in prototyping and testing the summarization algorithm.  ... 
doi:10.1108/02635570810847608 fatcat:dfqr5r2x3zef3gyaargzf35b74

TIARA

Shixia Liu, Michelle X. Zhou, Shimei Pan, Yangqiu Song, Weihong Qian, Weijia Cai, Xiaoxiao Lian
2012 ACM Transactions on Intelligent Systems and Technology  
We first introduce an enhanced, LDA-based topic analysis technique that automatically derives a set of topics to summarize a collection of documents and their content evolution over time.  ...  Unlike existing work in visual text analytics, which focuses either on developing sophisticated text analytic techniques or inventing novel text visualization metaphors, ours tightly integrates state-of-the-art  ...  Second, TIARA uses a time-based visualization to explain text summarization results derived by its text analytic engine.  ... 
doi:10.1145/2089094.2089101 fatcat:apuad5rwybc5rfhqd3qggpmevq

A Suggestion on the LDA-Based Topic Modeling Technique Based on ElasticSearch for Indexing Academic Research Results

Mi Kim, Dosung Kim
2022 Applied Sciences  
Specific classification rules are applied based on vast amounts of data and the latest references to classify and search keywords.  ...  The search results can be classified and rearranged to suit academic research paper keywords by applying the restructured classification system and the LDA-based topic modeling technique.  ...  (LDA) model can be used to categorize and present the search results based on the automatically inputted keywords.  ... 
doi:10.3390/app12063118 fatcat:czicpprgb5dihcmw6epoygsf5e

Review of Text Reduction Algorithms and Text Reduction using Sentence Vectorization

Sneh Garg, Sunil Chhillar
2014 International Journal of Computer Applications  
The authentic keywords extraction is the primary target for any text reduction algorithm. The presented survey shows the primary algorithm used for document summarization based on keywords.  ...  Also, the work presents a novel approach for keywords identification and in turn text reduction based on words histogram, the no. of sentences containing the words and knowledge corpus.  ...  Further, the work is on using the keywords extraction based on synonyms so that the document could be scanned globally for the text summarization.  ... 
doi:10.5120/18806-0380 fatcat:dwaotp3dbnb3pfygg3bzz6cjhi
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