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| Title Details: | |
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Collaborative Filtering Algorithms |
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| Authors: |
Symeonidis, Panagiotis |
| Description: | |
| Abstract: |
In the second chapter we will focus on k-nearest neighbors based cooperative filtering (CF) algorithms. First, we will give an extensive description and analysis of the factors involved and influencing the SF (similarity measures, modalities, and the neighbourhood generation of the user/item under consideration etc.). We will then describe in detail the ways of generating the list of proposed elements. Finally, we will briefly present the ways of measuring the effectiveness (precision metrics, retrieval metrics etc.) of the recommendation algorithms.
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| Linguistic Editors: |
Sakellarios, Michalis |
| Technical Editors: |
Karatzidis, Dimitrios |
| Graphic Editors: |
Symeonidis, Panagiotis |
| Type: |
Chapter |
| Creation Date: | 29-05-2023 |
| Item Details: | |
| License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| Handle | http://hdl.handle.net/11419/9574 |
| Bibliographic Reference: | Symeonidis, P. (2023). Collaborative Filtering Algorithms [Chapter]. In Symeonidis, P. 2023. Intelligent Recommender Systems [Postgraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/9574 |
| Language: |
Greek |
| Is Part of: |
Intelligent Recommender Systems |
| Publication Origin: |
Kallipos, Open Academic Editions |