贫困
发表于 2025-3-28 15:00:53
Listener-Aware Music Recommendation from Sensor and Social Media Dataindings on the topics of tailoring music recommendations to individual listeners and to groups of listeners sharing certain characteristics. We focus on two tasks: . (also known as serial recommendation) using sensor data and . using social media data.
Anal-Canal
发表于 2025-3-28 19:29:22
Logic-Based Incremental Process Miningful framework for supporting all of the above. This paper presents a First-Order Logic incremental method for inferring process models. Its efficiency and effectiveness were proved with both controlled experiments and a real-world dataset.
miniature
发表于 2025-3-29 02:35:31
978-3-319-23460-1Springer International Publishing Switzerland 2015
beta-cells
发表于 2025-3-29 03:05:54
Machine Learning and Knowledge Discovery in Databases978-3-319-23461-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
remission
发表于 2025-3-29 08:35:58
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avarice
发表于 2025-3-29 12:40:49
Bayesian Hypothesis Testing in Machine LearningMost hypothesis testing in machine learning is done using the frequentist null-hypothesis significance test, which has severe drawbacks. We review recent Bayesian tests which overcome the drawbacks of the frequentist ones.
Bernstein-test
发表于 2025-3-29 19:15:37
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招致
发表于 2025-3-29 21:08:43
Conference proceedings 2015ence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
MITE
发表于 2025-3-30 01:47:36
0302-9743 n and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.978-3-319-23460-1978-3-319-23461-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
羽饰
发表于 2025-3-30 05:51:40
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