The Geometry of Information Retrieval
Information retrieval, IR, the science of extracting information from any potential source, can be viewed in a number of ways: logical, probabilistic and vector space models are some of the most important. In this book, the author, one of the leading researchers in the area, shows how these views can be reforged in the same framework used to formulate the general principles of quantum mechanics. All the usual quantum-mechanical notions have their IR-theoretic analogues, and the standard results can be applied to address problems in IR, such as pseudo-relevance feedback, relevance feedback and ostensive retrieval. The relation with quantum computing is also examined. To keep the book self-contained appendices with background material on physics and mathematics are included. Each chapter ends with bibliographic remarks that point to further reading. This is an important, ground-breaking book, with much new material, for all those working in IR, AI and natural language processing.
- Leading figure in subject presents new, unifying framework for information retrieval, with a theory of measurement for artificial systems motivated by analogies with quantum mechanics
- Self-contained, with extensive annotated bibliography and appendices outlining basic mathematics
- Serves as an introduction to formal IR and to the mathematics of quantum computation
Reviews & endorsements
' … a clearly written and thought-provoking book that has been a pleasure to read. It is highly recommended.' IAPR Newsletter
Product details
August 2004Hardback
9780521838054
164 pages
229 × 152 × 11 mm
0.39kg
Available
Table of Contents
- Preface
- Prologue
- 1. Introduction
- 2. On sets and kinds in IR
- 3. Vector and Hilbert spaces
- 4. Linear transformations, operators and matrices
- 5. Conditional logic in IR
- 6. The geometry of IR
- Appendix I. Linear algebra
- Appendix II. Quantum mechanics
- Appendix III. Probability
- Bibliography
- Index.