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180405 ||| eng |
| 020 |
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|a 9789811053733
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| 100 |
1 |
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|a Wu, Shu
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| 245 |
0 |
0 |
|a Context-Aware Collaborative Prediction
|h Elektronische Ressource
|c by Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Singapore
|b Springer Nature Singapore
|c 2017, 2017
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| 300 |
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|a XI, 69 p. 9 illus., 8 illus. in color
|b online resource
|
| 505 |
0 |
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|a 1. Introduction -- 2. Context-Aware Collaborative Prediction -- 3. Context Operation -- 4. Hierarchical Representation -- 5. Context-Aware Recurrent Structure -- 6. Performance of Different Collaborative Prediction Tasks
|
| 653 |
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|a Information Storage and Retrieval
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| 653 |
|
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|a Artificial Intelligence
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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| 653 |
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|a Information storage and retrieval systems
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| 653 |
|
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|a Artificial intelligence
|
| 653 |
|
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|a Data Mining and Knowledge Discovery
|
| 653 |
|
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|a Computer and Information Systems Applications
|
| 700 |
1 |
|
|a Liu, Qiang
|e [author]
|
| 700 |
1 |
|
|a Wang, Liang
|e [author]
|
| 700 |
1 |
|
|a Tan, Tieniu
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
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|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a SpringerBriefs in Computer Science
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-10-5373-3?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
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|a 025.04
|
| 520 |
|
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|a This book presents two collaborative prediction approaches based on contextual representation and hierarchical representation, and their applications including context-aware recommendation, latent collaborative retrieval and click-through rate prediction. The proposed techniques offer significant improvements over current methods, the key determinants being the incorporated contextual representation and hierarchical representation. To provide a background to the core ideas presented, it offers an overview of contextual modeling and the theory of contextual representation and hierarchical representation, which are constructed for the joint interaction of entities and contextual information. The book offers a rich blend of theory and practice, making it a valuable resource for students, researchers and practitioners who need to construct systems of information retrieval, data mining and recommendation systems with contextual information
|