图 书 馆开课单位--清华大学
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21Towards a Better Understanding of Query Reformulation Behavior in Web Search[更好地理解Web搜索中的查询重新格式化行为]
Jia Chen(清华大学) Towards a Better Understanding of Query Reformulation Behavior in Web Search
热度：24
Jia Chen(清华大学) Towards a Better Understanding of Query Reformulation Behavior in Web Search
热度：24
22CatchSync: Catching Synchronized Behavior in Large Directed Graphs[CatchSync：捕捉大型有向图中的同步行为]
Meng Jiang(清华大学) Given a directed graph of millions of nodes, how can we automatically spot anomalous, suspicious nodes, judging only from their connectivity patterns?...
热度：254
Meng Jiang(清华大学) Given a directed graph of millions of nodes, how can we automatically spot anomalous, suspicious nodes, judging only from their connectivity patterns?...
热度：254
23Multi-Label Ensemble Learning[多标签集成学习]
Wenbin Tang(清华大学) Multi-label learning aims at predicting potentially multiple labels for a given instance. Conventional multi-label learning approaches focus on exploi...
热度：172
Wenbin Tang(清华大学) Multi-label learning aims at predicting potentially multiple labels for a given instance. Conventional multi-label learning approaches focus on exploi...
热度：172
24Laplace Maximum Margin Markov Networks[拉普拉斯最大保证金马尔可夫网络]
Jun Zhu(清华大学) Learning sparse Markov networks based on the maximum margin principle remains an open problem in structured prediction. In this paper, we proposed the...
热度：124
Jun Zhu(清华大学) Learning sparse Markov networks based on the maximum margin principle remains an open problem in structured prediction. In this paper, we proposed the...
热度：124
25Multi-Stage Multi-Task Feature Learning[多阶段多任务特征学习]
Changshui Zhang(清华大学) Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfu...
热度：103
Changshui Zhang(清华大学) Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfu...
热度：103
26User Browsing Graph: Structure, Evolution and Application[用户浏览图：结构，演变和应用]
Min Zhang; Yijiang Jin;Shaoping Ma;Liyun Ru; Yiqun Liu(清华大学) This paper focuses on ‘user browsing graph’ which is constructed with users’ click-through behavior modeled with Web access logs. Us...
热度：33
Min Zhang; Yijiang Jin;Shaoping Ma;Liyun Ru; Yiqun Liu(清华大学) This paper focuses on ‘user browsing graph’ which is constructed with users’ click-through behavior modeled with Web access logs. Us...
热度：33
27Mining Research Topic-related Influence between Academia and Industry[学术界与产业界的相关研究课题]
Wenbin Tang(清华大学) Recently the problem of mining social influence has attracted lots of attention. Given a social network, researchers are interested in problems such a...
热度：31
Wenbin Tang(清华大学) Recently the problem of mining social influence has attracted lots of attention. Given a social network, researchers are interested in problems such a...
热度：31
28Learning to Infer Social Ties in Large Network[在大型网络中学习推断社会关系]
Wenbin Tang(清华大学) In online social networks, most relationships are lack of meaning labels (e.g., "colleague" and "intimate friends"), simply becaus...
热度：83
Wenbin Tang(清华大学) In online social networks, most relationships are lack of meaning labels (e.g., "colleague" and "intimate friends"), simply becaus...
热度：83
29Primal Sparse Max-Margin Markov Networks [原始稀疏的最大间隔马尔可夫网络]
Jun Zhu(清华大学) Max-margin Markov networks (M3N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3N enjoys ...
热度：110
Jun Zhu(清华大学) Max-margin Markov networks (M3N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3N enjoys ...
热度：110
30FEMA: Flexible Evolutionary Multi-faceted Analysis for Dynamic Behavioral Pattern Discovery[FEMA：动态行为模式发现的柔性进化多方面分析]
Meng Jiang(清华大学) Behavioral pattern discovery is increasingly being studied to understand human behavior and the discovered patterns can be used in many real world app...
热度：53
Meng Jiang(清华大学) Behavioral pattern discovery is increasingly being studied to understand human behavior and the discovered patterns can be used in many real world app...
热度：53