Graph-based natural language processing and information retrieval / Rada Mihalcea, Dragomir Radev.

Mihalcea, Rada, 1974-
Call Number
005.4/37
Author
Mihalcea, Rada, 1974- author.
Title
Graph-based natural language processing and information retrieval / Rada Mihalcea, Dragomir Radev.
Graph-based Natural Language Processing & Information Retrieval
Physical Description
1 online resource (viii, 192 pages) : digital, PDF file(s).
Notes
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Contents
Machine generated contents note: Part I. Introduction to Graph Theory: 1. Notations, properties, and representations; 2. Graph-based algorithms; Part II. Networks: 3. Random networks; 4. Language networks; Part III. Graph-Based Information Retrieval: 5. Link analysis for the world wide web; 6. Text clustering; Part IV. Graph-Based Natural Language Processing: 7. Semantics; 8. Syntax; 9. Applications.
Summary
Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.
Added Author
Radev, Dragomir, 1968- author.
Subject
NATURAL LANGUAGE PROCESSING (COMPUTER SCIENCE)
Graphical user interfaces (Computer systems)
Multimedia
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520
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Summary
Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.
Notes
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Contents
Machine generated contents note: Part I. Introduction to Graph Theory: 1. Notations, properties, and representations; 2. Graph-based algorithms; Part II. Networks: 3. Random networks; 4. Language networks; Part III. Graph-Based Information Retrieval: 5. Link analysis for the world wide web; 6. Text clustering; Part IV. Graph-Based Natural Language Processing: 7. Semantics; 8. Syntax; 9. Applications.
Subject
NATURAL LANGUAGE PROCESSING (COMPUTER SCIENCE)
Graphical user interfaces (Computer systems)
Multimedia