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Unveiling Correlations via Mining Human-Thing Interactions in the Web of Things
Lina Yao, Quan Z. Sheng, Anne H. H. Ngu, Xue Li, Boualem Benattalah
Article No.: 62
With recent advances in radio-frequency identification (RFID), wireless sensor networks, and Web services, physical things are becoming an integral part of the emerging ubiquitous Web. Finding correlations among ubiquitous things is a crucial...
As-You-Type Social Aware Search
Paul Lagrée, Bogdan Cautis, Hossein Vahabi
Article No.: 63
Modern search applications feature real-time as-you-type query search. In its elementary form, the problem consists in retrieving a set of k search results, that is, performing a search with a given prefix, and showing the top-ranked...
Transfer Learning for Behavior Ranking
Weike Pan, Qiang Yang, Yuchao Duan, Ben Tan, Zhong Ming
Article No.: 65
Intelligent recommendation has been well recognized as one of the major approaches to address the information overload problem in the big data era. A typical intelligent recommendation engine usually consists of three major components, that is,...
Homogeneity in Web Search Results: Diagnosis and Mitigation
Rakesh Agrawal, Behzad Golshan, Evangelos E. Papalexakis
Article No.: 66
Access to diverse perspectives nurtures an informed citizenry. Google and Bing have emerged as the duopoly that largely arbitrates which English-language documents are seen by web searchers. We present our empirical study over the search results...
Visual Classification of Furniture Styles
Zhenhen Hu, Yonggang Wen, Luoqi Liu, Jianguo Jiang, Richang Hong, Meng Wang, Shuicheng Yan
Article No.: 67
Furniture style describes the discriminative appearance characteristics of furniture. It plays an important role in real-world indoor decoration. In this article, we explore the furniture style features and study the problem of furniture style...
Adult Image and Video Recognition by a Deep Multicontext Network and Fine-to-Coarse Strategy
Xinyu Ou, Hefei Ling, Han Yu, Ping Li, Fuhao Zou, Si Liu
Article No.: 68
Adult image and video recognition is an important and challenging problem in the real world. Low-level feature cues do not produce good enough information, especially when the dataset is very large and has various data distributions. This issue...
DUCT: An Upper Confidence Bound Approach to Distributed Constraint Optimization Problems
Brammert Ottens, Christos Dimitrakakis, Boi Faltings
Article No.: 69
We propose a distributed upper confidence bound approach, DUCT, for solving distributed constraint optimization problems. We compare four variants of this approach with a baseline random sampling algorithm, as well as other complete and incomplete...