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樓主: 愚蠢地活
31#
發(fā)表于 2025-3-26 23:08:21 | 只看該作者
,John Fowles’s , and William Golding’s ,cally, we focus on collaborative filtering, content-based filtering, constraint-based, critiquing-based, and hybrid recommendation. Throughout this chapter, we differentiate between (1) . and (2) . as basic strategies for aggregating the preferences of individual group members.
32#
發(fā)表于 2025-3-27 04:35:34 | 只看該作者
33#
發(fā)表于 2025-3-27 09:11:13 | 只看該作者
34#
發(fā)表于 2025-3-27 11:58:08 | 只看該作者
https://doi.org/10.1007/978-3-642-49264-8cept of . and then discuss how preferences can be handled for different recommendation approaches. Furthermore, we sketch how to deal with inconsistencies such as contradicting preferences of individual users.
35#
發(fā)表于 2025-3-27 14:52:59 | 只看該作者
36#
發(fā)表于 2025-3-27 17:50:25 | 只看該作者
Algorithms for Group Recommendationcally, we focus on collaborative filtering, content-based filtering, constraint-based, critiquing-based, and hybrid recommendation. Throughout this chapter, we differentiate between (1) . and (2) . as basic strategies for aggregating the preferences of individual group members.
37#
發(fā)表于 2025-3-28 01:01:27 | 只看該作者
Evaluating Group Recommender Systemstechniques for group recommender systems are often the same or similar to those that are used for single user recommenders. We show how to apply these techniques on the basis of examples and introduce evaluation approaches that are specifically useful in group recommendation scenarios.
38#
發(fā)表于 2025-3-28 05:25:13 | 只看該作者
Group Recommender Applicationsmovies and TV programs, travel destinations and events, news and web pages, healthy living, software engineering, and domain-independent recommenders. Each application is analyzed with regard to the characteristics of group recommenders as introduced in Chap. ..
39#
發(fā)表于 2025-3-28 06:59:43 | 只看該作者
Handling Preferencescept of . and then discuss how preferences can be handled for different recommendation approaches. Furthermore, we sketch how to deal with inconsistencies such as contradicting preferences of individual users.
40#
發(fā)表于 2025-3-28 13:24:06 | 只看該作者
Further Choice Scenariosrios exist that differ in the way alternatives are represented and recommendations are determined. We introduce a categorization of these scenarios and discuss knowledge representation and group recommendation aspects on the basis of examples.
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