Statistical methods for recommender systems (Record no. 29648)
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| LIBRARY OF CONGRESS CONTROL NUMBER | |
|---|---|
| LC control number | 2015026092 |
| ISBN | |
| International Standard Book Number | 9781107036079 |
| DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Call number | 006.3/3 |
| MAIN ENTRY--PERSONAL AUTHOR | |
| Authors | Agarwal, Deepak K., |
| Dates | 1973- |
| TITLE STATEMENT | |
| Title | Statistical methods for recommender systems |
| Statement of responsibility, etc. | Deepak K. Agarwal, Bee Chung-Chen |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | New York, NY : |
| Publisher | Cambridge University Press, |
| Date | c2016. |
| PHYSICAL DESCRIPTION | |
| Extent | xii, 284 p. : |
| Other Details | ill. ; |
| Size | 24 cm. |
| BIBLIOGRAPHY, ETC. NOTE | |
| Note | Includes bibliographical references (p. 265-272) and index. |
| SUMMARY | |
| Summary | Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with. |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Recommender systems (Information filtering) |
| General | Statistical methods |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Expert systems (Computer science) |
| General | Statistical methods |
| ADDED ENTRY | |
| Personal name | Chung-Chen, Bee |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://uowd.box.com/s/vputfhdosh2virihawmxbswm3z4qgk21">https://uowd.box.com/s/vputfhdosh2virihawmxbswm3z4qgk21</a> |
| Public note | Location Map |
| MAIN ENTRY--PERSONAL AUTHOR | |
| -- | 39134 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 39135 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 39136 |
| ADDED ENTRY | |
| -- | 39137 |
| Date last seen | Total checkouts | Full call number | Barcode | Date last borrowed | Cost, replacement price | Price effective from | Koha item type | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Withdrawn status | Permanent location | Current location | Shelving location | Date acquired | Source of acquisition |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 27/07/2021 | 1 | 006.33 AG ST | T0054725 | 16/06/2019 | 34.99 | 26/01/2017 | REGULAR | Dewey Decimal Classification | University of Wollongong in Dubai | University of Wollongong in Dubai | Main Collection | 25/07/2016 | AMAUK |