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Titlebook: Advanced Data Mining and Applications; 10th International C Xudong Luo,Jeffrey Xu Yu,Zhi Li Conference proceedings 2014 Springer Internatio

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31#
發(fā)表于 2025-3-26 22:01:42 | 只看該作者
32#
發(fā)表于 2025-3-27 02:08:35 | 只看該作者
33#
發(fā)表于 2025-3-27 07:11:10 | 只看該作者
Joachim Emig,Ingeborg Titz-Matuszakts to some extent, since their tourism demands tend to be more personalized and dynamic. Based on the above motivations, we design and develop a personalized tourism system based on a novel cooperation crowdsourcing model through the Internet. More importantly, data quality control based on the crow
34#
發(fā)表于 2025-3-27 11:27:23 | 只看該作者
Bernhard August von Lindenau (1779-1854)rovide a set of . items that will be of interest. In many user-based collaborative filtering applications based on KNN(K nearest neighbor algorithm), they only use similarity information(cosine similarity) between users, in some case, they have not use the difference information, so the precision an
35#
發(fā)表于 2025-3-27 16:49:26 | 只看該作者
https://doi.org/10.1007/978-3-476-03393-2Recommender systems are used online to suggest items to users according to the users, expressed preferences. Yet, recommender systems will endorse an item regardless of its reputation value. In this paper, we report the incorporation of reputation models into recommender systems to enhance the accur
36#
發(fā)表于 2025-3-27 19:34:22 | 只看該作者
https://doi.org/10.1007/978-3-476-03393-2 samples. The methodology consists of 1) an extensive set of experiments to estimate the empirical distribution of performance of the population of all possible ensembles that can be created with those bootstraps and 2) a metalearning approach to analyze that distribution based on characteristics of
37#
發(fā)表于 2025-3-27 22:32:22 | 只看該作者
Die Bernhard Heinesche Sammlung,ecommendations to them. The context in which a choice is made has been recognized as an important factor for recommendation systems. Recently, researchers extend the classical matrix factorization and allows for a generic integration of contextual information by modeling the data as a tensor. Howeve
38#
發(fā)表于 2025-3-28 03:33:51 | 只看該作者
39#
發(fā)表于 2025-3-28 09:03:30 | 只看該作者
Geometrie, Physik, Philosophie,es. In this paper, we aim to discover animal movement patterns from animal trajectory data. In particular, we propose a notion of continuous activity pattern as the concise representation of underlying similar spatio-temporal movements, and develop an extension and refinement framework to discover t
40#
發(fā)表于 2025-3-28 14:07:43 | 只看該作者
https://doi.org/10.1007/978-3-319-14717-8Web service; cloud service; crowdsourcing; data mining; dynamic databases; ensemble learning; image hashin
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