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Titlebook: Web and Big Data; First International Lei Chen,Christian S. Jensen,Xiang Lian Conference proceedings 2017 Springer International Publishin

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51#
發(fā)表于 2025-3-30 08:22:13 | 只看該作者
Boost Clickbait Detection Based on User Behavior Analysis a classifier to produce an initial clickbait-score for articles. Then, we define a loss function on the user behavior and tune the clickbait score toward decreasing the loss function. Experiment shows that we improve precision and recall after using user behavior.
52#
發(fā)表于 2025-3-30 13:55:49 | 只看該作者
Boost Clickbait Detection Based on User Behavior Analysis a classifier to produce an initial clickbait-score for articles. Then, we define a loss function on the user behavior and tune the clickbait score toward decreasing the loss function. Experiment shows that we improve precision and recall after using user behavior.
53#
發(fā)表于 2025-3-30 16:53:47 | 只看該作者
54#
發(fā)表于 2025-3-30 21:01:36 | 只看該作者
55#
發(fā)表于 2025-3-31 03:03:34 | 只看該作者
Improving Topic Diversity in Recommendation Lists: Marginally or Proportionally?modular function maximization and proportionality respectively. Experimental results on MovieLens and FilmTrust datasets demonstrate that our approach outperforms state-of-the-art techniques in terms of distributional diversity.
56#
發(fā)表于 2025-3-31 07:41:31 | 只看該作者
Improving Topic Diversity in Recommendation Lists: Marginally or Proportionally?modular function maximization and proportionality respectively. Experimental results on MovieLens and FilmTrust datasets demonstrate that our approach outperforms state-of-the-art techniques in terms of distributional diversity.
57#
發(fā)表于 2025-3-31 12:22:42 | 只看該作者
58#
發(fā)表于 2025-3-31 14:15:33 | 只看該作者
59#
發(fā)表于 2025-3-31 19:27:25 | 只看該作者
Event2vec: Learning Representations of Events on Temporal SequencesFinally, we feed these data to embedding neural network to get learned vectors. Experiments on real temporal event sequence data in medical area demonstrate the effectiveness and efficiency of the proposed method. The procedure is totally unsupervised without the help of expert knowledge. Thus can b
60#
發(fā)表于 2025-4-1 00:52:53 | 只看該作者
Event2vec: Learning Representations of Events on Temporal SequencesFinally, we feed these data to embedding neural network to get learned vectors. Experiments on real temporal event sequence data in medical area demonstrate the effectiveness and efficiency of the proposed method. The procedure is totally unsupervised without the help of expert knowledge. Thus can b
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