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Titlebook: Web and Big Data; Second International Yi Cai,Yoshiharu Ishikawa,Jianliang Xu Conference proceedings 2018 Springer Nature Switzerland AG 20

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31#
發(fā)表于 2025-3-26 23:03:51 | 只看該作者
32#
發(fā)表于 2025-3-27 02:10:43 | 只看該作者
Xiaotian Han,Chuan Shi,Lei Zheng,Philip S. Yu,Jianxin Li,Yuanfu Luce; Turkey; and Cyprus. These are countries at the crossroads, in flux, whose peripheral siting at the centre of global capitalism provides unusual insight into the dark recesses of patriarchy, paternalism and exploitation.978-1-4039-7586-7978-1-4039-8148-6
33#
發(fā)表于 2025-3-27 08:28:32 | 只看該作者
Conference proceedings 2018lly reviewed and selected from 168 submissions.?The papers are organized around the following topics: Text Analysis, Social Networks, Recommender Systems, Information Retrieval, Machine Learning, Knowledge Graphs, Database and Web Applications, Data Streams, Data Mining and Application, Query Processing, Big Data and Blockchain..
34#
發(fā)表于 2025-3-27 12:15:11 | 只看該作者
Abstractive Summarization with the Aid of Extractive Summarizationextractive task to strengthen their consistency. Experiments on the CNN/DailyMail dataset demonstrate that both the auxiliary task and the attention constraint contribute to improve the performance significantly, and our model is comparable to the state-of-the-art abstractive models.
35#
發(fā)表于 2025-3-27 14:28:04 | 只看該作者
Abstractive Summarization with the Aid of Extractive Summarizationextractive task to strengthen their consistency. Experiments on the CNN/DailyMail dataset demonstrate that both the auxiliary task and the attention constraint contribute to improve the performance significantly, and our model is comparable to the state-of-the-art abstractive models.
36#
發(fā)表于 2025-3-27 19:11:35 | 只看該作者
37#
發(fā)表于 2025-3-27 22:30:52 | 只看該作者
38#
發(fā)表于 2025-3-28 04:40:52 | 只看該作者
39#
發(fā)表于 2025-3-28 07:34:08 | 只看該作者
Personalized Top-, Influential Community Search over Large Social Networkssuch networks, we first introduce a search space refinement method. We then present pruning based and heuristic based search approaches. The proposed algorithms more than double the efficiency of the search performance for basic solutions. The effectiveness and efficiency of our algorithms have been verified using four real datasets.
40#
發(fā)表于 2025-3-28 13:57:29 | 只看該作者
Matrix Factorization Meets Social Network Embedding for Rating Predictionin the variation in people’s feedback. Furthermore, the influence of different social network embedding strategies on our framework are compared. Experiments on three real datasets validate the effectiveness of the proposed solution.
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