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检索条件"机构=The Key Lab of Big Data Intelligent Computing of Zhejiang Province"
66 条 记 录,以下是61-70 订阅
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Community-Based question answering via heterogeneous social network learning  30
Community-Based question answering via heterogeneous social ...
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30th AAAI Conference on Artificial Intelligence, AAAI 2016
作者: Fang, Hanyin Wu, Fei Zhao, Zhou Duan, Xinyu Zhuang, Yueting Ester, Martin College of Computer Science Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University China School of Computing Science Simon Fraser University Canada
Community-based question answering (cQA) sites have accumulated vast amount of questions and corresponding crowdsourced answers over time. How to efficiently share the underlying information and knowledge from reliabl... 详细信息
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Metric All-k-Nearest-Neighbor Search
Metric All-k-Nearest-Neighbor Search
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作者: Chen, Lu Gao, Yunjun Chen, Gang Zhang, Haida College of Computer Science Zhejiang University 38 Zheda Road Hangzhou310027 China Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou China
An all-k-nearest-neighbor (AkNN) query finds from a given object set O, k nearest neighbors for each object in a specified query set Q. This operation is common in many applications such as GIS, data mining, and image... 详细信息
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Top-k Dominating Queries on Incomplete data
Top-k Dominating Queries on Incomplete Data
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作者: Miao, Xiaoye Gao, Yunjun Zheng, Baihua Chen, Gang Cui, Huiyong College of Computer Science Zhejiang University 38 Zheda Road Hangzhou310027 China Key Laboratory of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou China School of Information Systems Singapore Management University Singapore178902 Singapore
The top-k dominating (TKD) query returns the k objects that dominate the maximum number of objects in a given dataset. It combines the advantages of skyline and top-k queries, and plays an important role in many decis... 详细信息
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Answering why-not questions on metric probabilistic range queries
Answering why-not questions on metric probabilistic range qu...
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International Conference on data Engineering
作者: Lu Chen Yunjun Gao Kai Wang Christian S. Jensen Gang Chen College of Computer Science Zhejiang University Hangzhou China The Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou China Department of Computer Science Aalborg University Denmark
Metric probabilistic range queries (MPRQ) have received substantial attention due to their utility in multimedia and text retrieval, decision making, etc. Existing MPRQ studies generally aim to improve query efficienc... 详细信息
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SI2P: A restaurant recommendation system using preference queries over incomplete information  42
SI2P: A restaurant recommendation system using preference qu...
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42nd International Conference on Very Large data Bases, VLDB 2016
作者: Miao, Xiaoye Gao, Yunjun Chen, Gang Cui, Huiyong Guo, Chong Pan, Weida College of Computer Science Zhejiang University Hangzhou China The Key Lab of Big Data Intelligent Computing of Zhejiang Province Zhejiang University Hangzhou China
The incomplete data is universal in many real-life applications due to data integration, the limitation of devices, etc. In this demonstration, we present SI2P, a restaurant recommendation System with Preference queri... 详细信息
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Flickr group recommendation via heterogeneous information networks  15
Flickr group recommendation via heterogeneous information ne...
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7th International Conference on Internet Multimedia computing and Service, ICIMCS 2015
作者: Wang, Yueyang Xia, Yuanfang Tang, Siliang Wu, Fei Zhuang, Yueting College of Computer Science and Technology Zhejiang University Key Laboratory of Big Data Intelligent Computing of Zhejiang Province Innovation Joint Research Center for ICPS China
As an important characteristic of social media (i.e. Flickr or Facebook), user communities or groups are beginning to attract increasing attention. Most of the previous studies on group recommendation only consider a ... 详细信息
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