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Library of Congress Subject Headings
  • Language: en
  • Pages: 1512
F-O
  • Language: en
  • Pages: 1636

F-O

  • Type: Book
  • -
  • Published: 1990
  • -
  • Publisher: Unknown

None

Library of Congress Subject Headings: F-O
  • Language: en
  • Pages: 1534

Library of Congress Subject Headings: F-O

  • Type: Book
  • -
  • Published: 1989
  • -
  • Publisher: Unknown

None

Library of Congress Subject Headings
  • Language: en
  • Pages: 1622
A-E
  • Language: en
  • Pages: 1548

A-E

  • Type: Book
  • -
  • Published: 1990
  • -
  • Publisher: Unknown

None

Introduction to Information Retrieval
  • Language: en

Introduction to Information Retrieval

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Library of Congress Subject Headings: P-Z
  • Language: en
  • Pages: 1436
Information Retrieval: Uncertainty and Logics
  • Language: en
  • Pages: 332

Information Retrieval: Uncertainty and Logics

In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general th...

An Introduction to Neural Information Retrieval
  • Language: en
  • Pages: 142

An Introduction to Neural Information Retrieval

Efficient Query Processing for Scalable Web Search will be a valuable reference for researchers and developers working on This tutorial provides an accessible, yet comprehensive, overview of the state-of-the-art of Neural Information Retrieval.