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Review On Abstractive Text Summarization Techniques For Biomedical Domain

Patel Krutika, Desai Urmi
2018 Zenodo  
Automatic text summarization provides solution by generating summary automatically. Text summarization techniques classified into extractive and abstractive text summarization types.  ...  Abstractive text summarization can solve this problem by representing the extracted sentences into another understandable semantic form.  ...  Related Work This section gives a detailed description of various abstractive text summarization techniques.  ... 
doi:10.5281/zenodo.1252402 fatcat:6khvqb535jamdnk3abc4jra3ui

Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm

Elham Mahdipour
2014 International Journal of Intelligent Information Systems  
In this paper, the proposed Persian text summarizer system employs combination of graph-based and the TF-IDF methods after word stemming in order to weight the sentences.  ...  Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains.  ...  W i,j =tf i,j *isf i (3) Related Works Research studies in non-Persian languages domain considers challenges of automatic text summarization and related works to 2009 [3] .  ... 
doi:10.11648/j.ijiis.s.2014030601.26 fatcat:qo7bgzwszrcbhn6x4mr4cr3tky

Automatic Summarization of Scientific Articles: A Survey

Nouf Ibrahim Altmami, Mohamed El Bachir Menai
2020 Journal of King Saud University: Computer and Information Sciences  
The automatic summarization of scientific articles differs from the summarization of generic texts due to their specific structure and inclusion of citation sentences.  ...  Automatically summarizing scientific articles would help researchers in their investigation by speeding up the research process.  ...  Related work summarization The related work section of a scientific article is usually used to show the distinctions and points of interest of the current work compared with those of previous research  ... 
doi:10.1016/j.jksuci.2020.04.020 fatcat:zklevq5hkndd7c6p3zazrf5bum

Resolving ambiguity in biomedical text to improve summarization

Laura Plaza, Mark Stevenson, Alberto Díaz
2012 Information Processing & Management  
Access to the vast body of research literature that is now available on biomedicine and related fields can be improved with automatic summarization.  ...  This paper describes a summarization system for the biomedical domain that represents documents as graphs formed from concepts and relations in the UMLS Metathesaurus.  ...  The graph-based algorithm for summarization algorithm (Section 3) is similar to Personalized PageRank, a graph-based WSD algorithm (Section 4.2).  ... 
doi:10.1016/j.ipm.2011.09.005 fatcat:zlkllbimbbatteasqry6ummtju

Visual Summarization of Scholarly Videos Using Word Embeddings and Keyphrase Extraction [chapter]

Hang Zhou, Christian Otto, Ralph Ewerth
2019 Lecture Notes in Computer Science  
In this paper, we present an approach that generates a visual summary of video content based on semantic word embeddings and keyphrase extraction.  ...  For this purpose, we exploit video annotations that are automatically generated by speech recognition and video OCR (optical character recognition).  ...  Visual Summarization of Scientific Video Content In this section, we describe our approach for video content summarization solely based on textual information.  ... 
doi:10.1007/978-3-030-30760-8_28 fatcat:hr4cw4osprfzhar3tgznhblxqu

Layout Aware Semantic Element Extraction for Sustainable Science & Technology Decision Support

Hyuntae Kim, Jongyun Choi, Soyoung Park, Yuchul Jung
2022 Sustainability  
Moreover, to constructing a scientific knowledge graph consisting of multiple S&T documents, we newly defined an extensible Semantic Elements Knowledge Graph (SEKG) structure.  ...  In addition, to illustrate the potential power of our SEKG, we provide two promising application scenarios, such as a scientific knowledge guide across multiple S&T documents and questions and answering  ...  Conflicts of Interest: The authors declare no conflict of interest. Sustainability 2022, 14, 2802  ... 
doi:10.3390/su14052802 fatcat:eew4bb5q55ccpavk6yxroogsgq

Neural Related Work Summarization with a Joint Context-driven Attention Mechanism [article]

Yongzhen Wang, Xiaozhong Liu, Zheng Gao
2019 arXiv   pre-print
Conventional solutions to automatic related work summarization rely heavily on human-engineered features.  ...  Our motivation is to maintain the topic coherency between a related work section and its target document, where both the textual and graphic contexts play a big role in characterizing the relationship  ...  This work is partially supported by the National Science Foundation of China under grant No. 71271034.  ... 
arXiv:1901.09492v1 fatcat:nwyplxa2u5gmpez3ic6wydfgne

Neural Related Work Summarization with a Joint Context-driven Attention Mechanism

Yongzhen Wang, Xiaozhong Liu, Zheng Gao
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Conventional solutions to automatic related work summarization rely heavily on humanengineered features.  ...  Our motivation is to maintain the topic coherency between a related work section and its target document, where both the textual and graphic contexts play a big role in characterizing the relationship  ...  This work is partially supported by the National Science Foundation of China under grant No. 71271034.  ... 
doi:10.18653/v1/d18-1204 dblp:conf/emnlp/WangLG18 fatcat:5u3y6mv7kjgddihhfdwvdxv2ra

The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link Network

Mengyun Cao, Xiaoping Sun, Hai Zhuge, Marta Sales-Pardo
2018 PLoS ONE  
on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated.  ...  content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing.  ...  at Chinese Academy of Sciences, and University of Chinese Academy of Sciences.  ... 
doi:10.1371/journal.pone.0199303 pmid:29928017 pmcid:PMC6013162 fatcat:k7tkc62ef5ecre74syktg233cq

An Automatic Multidocument Text Summarization Approach Based on Naïve Bayesian Classifier Using Timestamp Strategy

Nedunchelian Ramanujam, Manivannan Kaliappan
2016 The Scientific World Journal  
Nowadays, automatic multidocument text summarization systems can successfully retrieve the summary sentences from the input documents.  ...  This paper introduces a new concept of timestamp approach with Naïve Bayesian Classification approach for multidocument text summarization.  ...  Conflict of Interests The authors declare that they have no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2016/1784827 pmid:27034971 pmcid:PMC4789525 fatcat:nm3unmc7m5bpfkf65obuwzyqym

Comparing different knowledge sources for the automatic summarization of biomedical literature

Laura Plaza
2014 Journal of Biomedical Informatics  
Objective:: Automatic summarization of biomedical literature usually relies on domain knowledge from external sources to build rich semantic representations of the documents to be summarized.  ...  concepts, and different types of relationships (co-occurrence and semantic relations from the UMLS Metathesaurus and Semantic Network) are used to link the concepts in the graph.  ...  A semantic graph-based summarizer The summarization system used for our experiments is based on the work presented in [24] .  ... 
doi:10.1016/j.jbi.2014.07.014 pmid:25066773 fatcat:hw6z3w64nrdfvaa2hysn5bvlqu

Text Summarization Using FrameNet-Based Semantic Graph Model

Xu Han, Tao Lv, Zhirui Hu, Xinyan Wang, Cong Wang
2016 Scientific Programming  
This paper proposes a Semantic Graph Model which exploits the semantic information of sentence using FSGM. FSGM treats sentences as vertexes while the semantic relationship as the edges.  ...  Text summarization is to generate a condensed version of the original document.  ...  Acknowledgments This work is supported by Basic Research of the Ministry of Science and Technology, China (2013FY114000).  ... 
doi:10.1155/2016/5130603 fatcat:pqzfq5m6ovhm7b4nyr7p6is54i

Multi-document Summarization via Deep Learning Techniques: A Survey [article]

Congbo Ma, Wei Emma Zhang, Mingyu Guo, Hu Wang, Quan Z. Sheng
2021 arXiv   pre-print
Multi-document summarization (MDS) is an effective tool for information aggregation that generates an informative and concise summary from a cluster of topic-related documents.  ...  Our survey, the first of its kind, systematically overviews the recent deep learning based MDS models.  ...  In this article, we select, summarize, discuss, and analyze 30 representative works. We used Google Scholar as the main search engine to discover related works.  ... 
arXiv:2011.04843v3 fatcat:zfi52xxef5g2tjkaw6hgjpwa5i

Review and Comparative Analysis of Topic Identification Techniques

Deepti Sehrawat, Maharshi Dayanand University, Rohtak, Haryana (India)
2019 International Journal of Advanced Trends in Computer Science and Engineering  
Existing solutions include text clustering, latent semantic approach, probabilistic latent semantics approach, latent Dirichlet allocation approach, association rule-based approaches, document clustering  ...  Topic identification is an area of data mining that finds common text/ themes from several documents. It is a data summarization technique that helps to summarize documents.  ...  In Section 3, we have presented related work carried out over the years by different researchers along with their pros and cons. Section 4 concludes the paper.  ... 
doi:10.30534/ijatcse/2019/71832019 fatcat:g46lyzxg7jcehlci4r62nxbtpe

Trends in Multi-document Summarization System Methods

Abimbola Soriyan, Theresa Omodunbi
2014 International Journal of Computer Applications  
Automatic summarization helps in mining data and delivering timely and cogent information to users. These systems attempt to address the issue of data mining using different summarization methods.  ...  This paper discusses existing methods and state of the art in automatic summarisation system from recent articles. Achievement and challenges involve are also discussed.  ...  The next section of the paper will explain related work of automatic summarization (AS) system including techniques employed, challenges in summarization automation will be discussed in section three.  ... 
doi:10.5120/17095-7804 fatcat:vlbwccop3rhftiwanojwkaqfia
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