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E-raamat: Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding

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"This book evaluates some of the existing approaches to information retrieval and summarization of digital documents, as well as highlighting current research and future developments"--

Computer scientists and others involved with language processing explore the current state of general-purpose and domain-specific document summarization methods, social networks and web news summarization, and multilingual summarization. Their topics include the classification of sentence ranking methods for multi-document summarization, interactive summaries by multi-pole information extraction for the archaeological domain, evaluation metrics for the summarization task, novel text summarization techniques for contextual advertising, new formats and interfaces for multi-document summarization and evaluation, aspects of multilingual news summarization, and language-independent summarization approaches. Annotation ©2014 Book News, Inc., Portland, OR (booknews.com)

The prevalence of digital documentation presents some pressing concerns for efficient information retrieval in the modern age. Readers want to be able to access the information they desire without having to search through a mountain of unrelated data, so algorithms and methods for effectively seeking out pertinent information are of critical importance. Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding evaluates some of the existing approaches to information retrieval and summarization of digital documents, as well as current research and future developments. This book serves as a sounding board for students, educators, researchers, and practitioners of information technology, advancing the ongoing discussion of communication in the digital age.
Foreword xv
Preface xvi
Acknowledgment xx
Section 1 General-Purpose and Domain-Specific Methods
Chapter 1 Classification of Sentence Ranking Methods for Multi-Document Summarization
1(27)
Sean Sovine
Hyoil Han
Chapter 2 Multi-Document Summarization by Extended Graph Text Representation and Importance Refinement
28(26)
Uri Mirchev
Mark Last
Chapter 3 Efficient Summarization with Polytopes
54(21)
Marina Litvak
Natalia Vanetik
Chapter 4 Interactive Summaries by Multi-Pole Information Extraction for the Archaeological Domain
75(22)
Angela Locoro
Massimo Ancona
Chapter 5 Evaluation Metrics for the Summarization Task
97(42)
Paulo Cesar Fernandes de Oliveira
Section 2 Social Networks and Web News Summarization
Chapter 6 Social Network Integration in Document Summarization
139(24)
Atefeh Farzindar
Chapter 7 Approaches to Large-Scale User Opinion Summarization for the Web
163(22)
William Darling
Chapter 8 Novel Text Summarization Techniques for Contextual Advertising
185(20)
Giuliano Armano
Alessandro Giuliani
Chapter 9 NewSum: "N-Gram Graph"-Based Summarization in the Real World
205(26)
George Giannakopoulos
George Kiomourtzis
Vangelis Karkaletsis
Chapter 10 New Formats and Interfaces for Multi-Document News Summarization and its Evaluation
231(26)
Bettina Berendt
Mark Last
Ilija Subasic
Mathias Verbeke
Section 3 Multilingual Summarization
Chapter 11 Multilingual Summarization Approaches
257(20)
Kamal Sarkar
Chapter 12 Aspects of Multilingual News Summarisation
277(18)
Josef Steinberger
Ralf Steinberger
Hristo Tanev
Vanni Zavarella
Marco Turchi
Chapter 13 Language Independent Summarization Approaches
295(13)
Firas Hmida
Compilation of References 308(25)
About the Contributors 333(6)
Index 339
Alessandro Fiori received the European Ph.D. degree from Politecnico di Torino, Italy. He is project manager at the Institute for Cancer Research and Treatment (IRCC) of Candiolo, Italy since January 2012. His research interests are in the field of data mining, in particular bioinformatics and text mining. His activity is focused on the development of information systems and analysis frameworks oriented to the management and integration of biological and molecular data. His research activities are also devoted to text summarisation and social network analysis.