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Titlebook: Web Technologies and Applications; APWeb 2016 Workshops Atsuyuki Morishima,Rong Zhang,Zhiwei Zhang Conference proceedings 2016 Springer Int

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樓主: 武士精神
21#
發(fā)表于 2025-3-25 05:22:43 | 只看該作者
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發(fā)表于 2025-3-25 22:47:46 | 只看該作者
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發(fā)表于 2025-3-26 04:06:08 | 只看該作者
Confirmatory Analysis on Influencing Factors When Mention Users in Twitterntioning users in a tweet, they will receive notifications and their possible retweets may help to initiate large cascade diffusion of the tweet. To enhance a tweet’s diffusion by finding the right persons to mention, in this paper, we propose three factors that probably have impact on tweet’s diffu
27#
發(fā)表于 2025-3-26 07:50:35 | 只看該作者
A Stock Recommendation Strategy Based on M-LDA Modelssive research reports quickly and accurately, and make a good stock recommendation method is one of the important issues in big data quantitative investment. Based on a kind of semi-supervised topic models (M-LDA) and by setting some fundamental emotion labels along with some certain topic labels,
28#
發(fā)表于 2025-3-26 10:16:13 | 只看該作者
Short-Term Forecasting and Application About Indoor Cooling Load Based on EDA-PSO-BP Algorithme used PSO optimization algorithm combined with BP neural network to do cooling load prediction experiments of indoor sample data of a building. The results showed that compared with other three kinds of prediction algorithms, the error of this algorithm is minimum and its running speed is the faste
29#
發(fā)表于 2025-3-26 13:55:40 | 只看該作者
Identifying Relevant Subgraphs in Large Networks subgraphs in large networks. Relevant subgraphs in large networks contain network elements which are maintained by network administrators. We formalize the problem and propose a framework consisting of two major phases. The relevance scores of all vertex pairs are computed in the offline phase, whi
30#
發(fā)表于 2025-3-26 20:48:21 | 只看該作者
User-Dependent Multi-relational Community Detection in Social Networkslational. In this paper, we propose a user-dependent method to detect communities in multi-relational social networks. We define a multi-relational community as a shared community over multiple single-relational graphs while the quality of a partitioning of nodes is assessed by a multi-relational mo
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