Information Retrieval Models (Record no. 85094)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03739nam a22004575i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-02328-6 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730163903.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220601s2013 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031023286 |
| -- | 978-3-031-02328-6 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 004.6 |
| 100 1# - AUTHOR NAME | |
| Author | Roelleke, Thomas. |
| 245 10 - TITLE STATEMENT | |
| Title | Information Retrieval Models |
| Sub Title | Foundations & Relationships / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2013. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXI, 141 p. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Synthesis Lectures on Information Concepts, Retrieval, and Services, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | List of Figures -- Preface -- Acknowledgments -- Introduction -- Foundations of IR Models -- Relationships Between IR Models -- Summary & Research Outlook -- Bibliography -- Author's Biography -- Index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the main instantiation of the PRF/BIR), and language modelling (LM). Also, the early 2000s saw the arrival of divergence from randomness (DFR). Regarding intuition and simplicity, though LM is clear from a probabilistic point of view, several people stated: "It is easy to understand TF-IDF and BM25. For LM, however, we understand the math, but we do not fully understand why it works." This book takes a horizontal approach gathering the foundations of TF-IDF, PRF, BIR, Poisson, BM25, LM, probabilistic inference networks (PIN's), and divergence-basedmodels. The aim is to create a consolidated and balanced view on the main models. A particular focus of this book is on the "relationships between models." This includes an overview over the main frameworks (PRF, logical IR, VSM, generalized VSM) and a pairing of TF-IDF with other models. It becomes evident that TF-IDF and LM measure the same, namely the dependence (overlap) between document and query. The Poisson probability helps to establish probabilistic, non-heuristic roots for TF-IDF, and the Poisson parameter, average term frequency, is a binding link between several retrieval models and model parameters. Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Foundations of IR Models / Relationships Between IR Models / Summary & Research Outlook / Bibliography / Author's Biography / Index. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-02328-6 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
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| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2013. |
| 336 ## - | |
| -- | text |
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| -- | rdacontent |
| 337 ## - | |
| -- | computer |
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| -- | rdamedia |
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| -- | online resource |
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| -- | text file |
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| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Communication Networks. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 1947-9468 |
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| -- | ZDB-2-SXSC |
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