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Books on the topic 'Text summarization'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

Torres-Moreno, Juan-Manuel. Automatic Text Summarization. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119004752.

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2

Inderjeet, Mani, and Maybury Mark T, eds. Advances in automatic text summarization. Cambridge, Mass: MIT Press, 1999.

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3

Kedzie, Christopher. Salience Estimation and Faithful Generation: Modeling Methods for Text Summarization and Generation. [New York, N.Y.?]: [publisher not identified], 2021.

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4

H, Hovy Eduard, Radev Dragomir, and AAAI Symposium (1998 : Stanford, California), eds. Intelligent text summarization: Papers from the 1998 AAAI Symposium, March 23-25, Stanford, California. Menlo Park, Calif: AAAI Press, 1998.

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5

Marcu, Constantin Daniel. The rhetorical parsing, summarization, and generation of natural language texts. Toronto: University of Toronto, Dept. of Computer Science, 1998.

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6

Hovy, Eduard. Text Summarization. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0032.

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This article describes research and development on the automated creation of summaries of one or more texts. It defines the concept of summary and presents an overview of the principal approaches in summarization. It describes the design, implementation, and performance of various summarization systems. The stages of automated text summarization are topic identification, interpretation, and summary generation, each having its sub stages. Due to the challenges involved, multi-document summarization is much less developed than single-document summarization. This article reviews particular techniques used in several summarization systems. Finally, this article assesses the methods of evaluating summaries. This article reviews evaluation strategies, from previous evaluation studies, to the two-basic measures method. Summaries are so task and genre specific; therefore, no single measurement covers all cases of evaluation

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7

Torres-Moreno, Juan Manuel. Automatic Text Summarization. Wiley & Sons, Incorporated, John, 2014.

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8

Torres-Moreno, Juan-Manuel. Automatic Text Summarization. Wiley & Sons, Incorporated, John, 2014.

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9

Torres-Moreno, Juan-Manuel. Automatic Text Summarization. Wiley-Interscience, 2014.

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10

Torres-Moreno, Juan-Manuel. Automatic Text Summarization. Wiley & Sons, Incorporated, John, 2014.

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11

Moreno, Juan Manuel Torres. Automatic Text Summarization. Wiley & Sons, Incorporated, John, 2014.

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12

Zhang, Renxian. Coherence-Targeted Text Summarization. Springer, 2020.

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13

Fiori, Alessandro. Trends and Applications of Text Summarization Techniques. IGI Global, 2020.

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14

Fiori, Alessandro. Trends and Applications of Text Summarization Techniques. IGI Global, 2019.

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15

Fiori, Alessandro. Trends and Applications of Text Summarization Techniques. IGI Global, 2019.

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16

Fiori, Alessandro. Trends and Applications of Text Summarization Techniques. IGI Global, 2019.

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17

Fiori, Alessandro. Trends and Applications of Text Summarization Techniques. IGI Global, 2019.

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18

Zhuge, Hai. Multi-Dimensional Summarization in Cyber-Physical Society. Elsevier Science & Technology Books, 2016.

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19

Zhuge, Hai. Multi-Dimensional Summarization in Cyber-Physical Society. Elsevier Science & Technology Books, 2016.

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20

Umamaheswari, K., and V. Priya. Computational Techniques for Text Summarization Based on Cognitive Intelligence. Taylor & Francis Group, 2023.

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21

Umamaheswari, K., and V. Priya. Computational Techniques for Text Summarization Based on Cognitive Intelligence. Taylor & Francis Group, 2023.

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22

Umamaheswari, K., and V. Priya. Computational Techniques for Text Summarization Based on Cognitive Intelligence. Taylor & Francis Group, 2023.

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23

Innovative Document Summarization Techniques Revolutionizing Knowledge Understanding. Idea Group,U.S., 2014.

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24

Artificial intelligence and text-understanding: Plot units and summarization procedures. Parma: Edizioni Zara, 1985.

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25

Intelligent Text Summarization: Papers Form the Aaai Spring Symposium (Technical Reports Vol. Ss-98-06). Amer Assn for Artificial, 1998.

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26

Hirschman, Lynette, and Inderjeet Mani. Evaluation. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0022.

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The commercial success of natural language (NL) technology has raised the technical criticality of evaluation. Choices of evaluation methods depend on software life cycles, typically charting four stages — research, advance prototype, operational prototype, and product. At the prototype stage, embedded evaluation can prove helpful. Analysis components can be loose grouped viz., segmentation, tagging, extracting information, and document threading. Output technologies such as text summarization can be evaluated in terms of intrinsic and extrinsic measures, the former checking for quality and informativeness and the latter, for efficiency and acceptability, in some tasks. ‘Post edit measures’ commonly used in machine translation, determine the amount of correction required to obtain a desirable output. Evaluation of interactive systems typically evaluates the system and the user as one team and deploys subject variability, which runs enough subjects to obtain statistical validity hence, incurring substantial costs. Evaluation being a social activity, creates a community for internal technical comparison, via shared evaluation criteria.

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27

Connell, Francis J., and David Sharrock. Baltimore Catechism and Mass No. 3: The Text of the Official Revised Edition 1949 with Summarizations of Doctrine and Study Helps. Seraphim Company Inc., 1995.

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