Similarity Function With Temporal Factor In Collaborative Filtering
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2012, 2012
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 42.64
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Add to basketItem description from seller
This item is printed on demand - it takes 3-4 days longer - Neuware -Similarity function is the key to accuracy of collaborative filtering algorithms. Adding a time factor to it addresses the problem of handling the web data efficiently as it is highly dynamic in nature. The data used in collaborative filtering algorithms is collected over as long period of time, in the form of feedbacks, clicks, etc. The interest of user or popularity of an item tends to change as new seasons, moods or festivals. The similarity function with temporal factor can efficiently handle the dynamics of web data as it captures and assigns weightage to the data. More recent data is given more weightage when similarity is calculated. in this way, the recent trends and older and obsolete data values are discarded when new unobserved items are predicted using collaborative filtering algorithms. Hence, better results and more accuracy. 56 pp. Englisch.
Seller Inventory # 9783659179952
- Title
- Similarity Function With Temporal Factor In Collaborative Filtering
- Author
- Meghna Khatri
- Publisher
- LAP LAMBERT Academic Publishing Jul 2012
- Publication year
- 2012
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3659179957
- ISBN 13
- 9783659179952
- Item weight
- 102 grams
- Dimensions
- 220x150x4 mm
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
Shipping rates from Germany to U.S.A.
| Item | 5 to 15 business days | 5 to 15 business days |
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