Graph Based Natural Language Processing by Mihalcea Rada (13 results)

Hardcover. Condition: Very Good. This book is in very good condition; no remainder marks. Appears to have been gently used. Inside pages are clean. ; 6.25 X 0.5 X 9.25 inches; 202 pages.

Condition: New.

Original decorated boards. Condition: Very Good. Reprint. With diagrams. Light wear to spine, covers & corners. ; 8vo; 192 pages.

Condition: New. In.

Condition: New. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Num Pages: 202 pages, 136 b/w illus. 11 tables. BIC Classification: UNH; UYQL. Category: (P) Professional & Vocational. Dimension: 236 x 165 x 11. Weight in Grams: 436. . 2011. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval.

Condition: New. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Num Pages: 202 pages, 136 b/w illus. 11 tables. BIC Classification: UNH; UYQL. Category: (P) Professional & Vocational. Dimension: 236 x 165 x 11. Weight in Grams: 436. . 2011. 1st Edition. Hardcover. . . . .

Hardcover. Condition: new. Hardcover. 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. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Readers will come away with a firm understanding of the major methods and applications of these topics that rely on graph-based representations and algorithms. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: Brand New. 1st edition. 208 pages. 9.25x6.25x0.50 inches. In Stock. This item is printed on demand.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Hardcover. Condition: new. Hardcover. 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. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Readers will come away with a firm understanding of the major methods and applications of these topics that rely on graph-based representations and algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Readers will come away with a firm understanding of the major methods and applications of these topics that rely on graph-based represe.

Hardcover. Condition: new. Hardcover. 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. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. Readers will come away with a firm understanding of the major methods and applications of these topics that rely on graph-based representations and algorithms. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.