By Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
This two-volume set, LNAI 9077 + 9078, constitutes the refereed complaints of the nineteenth Pacific-Asia convention on Advances in wisdom Discovery and knowledge Mining, PAKDD 2015, held in Ho Chi Minh urban, Vietnam, in may possibly 2015.
The complaints include 117 paper conscientiously reviewed and chosen from 405 submissions. they've been prepared in topical sections named: social networks and social media; class; computer studying; functions; novel equipment and algorithms; opinion mining and sentiment research; clustering; outlier and anomaly detection; mining doubtful and obscure info; mining temporal and spatial facts; characteristic extraction and choice; mining heterogeneous, high-dimensional and sequential info; entity answer and topic-modeling; itemset and high-performance facts mining; and recommendations.
Read Online or Download Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I PDF
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Extra resources for Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I
E. @Alex of all posts in Pe . We ﬁnally extract 28 features of four categories in total. We also normalize the topic and emotional features by text length. What Is New in Our City? A Framework for Event Extraction 23 Fig. 2. Five sampled Instagram photos from a detected Knicks NBA game event in NYC. From journalists’ perspective, the ﬁrst three images are considered representative to summarize the event. Although the last two images were uploaded at the stadium and their captions are also about game, they are not informative for describing this event.
The contributions made in this study are summarized as follows. – For socialization activity organization, we propose to model the existing friendship and the potential friendship in a heterogeneous social graph and formulate a new problem, namely, Hop-bounded Maximum Group Friending (HMGF), for ﬁnding suitable attendees. -Y. Shen et al. the ﬁrst problem that considers these two important relationships between attendees for activity organization. – We prove that HMGF is NP-Hard and there exists no approximation algorithm for HMGF unless P = N P .
Besides disasters,  use twitter posts to detect local festivals by monitoring the movements of crowds. Twitterstand  classiﬁes tweets as news and non-news to detect news events. Diﬀerent from these methods, our proposed framework is not restricted to any event type. Considering the data source, most of the previous works collect data from Twitter posts . We put two data collectors in Instagram and Twitter monitoring and collecting useful information from the live post streams from these two social media platforms.