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Displaying 1-10 out of 10 total
Discriminative Feature Selection by Nonparametric Bayes Error Minimization
Found in: IEEE Transactions on Knowledge and Data Engineering
By Shuang-Hong Yang,Bao-Gang Hu
Issue Date:August 2012
pp. 1422-1434
Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection algorithms, this paper presents a theoretically optimal criterion, namely, the d...
 
The first workshop on user engagement optimization
Found in: Proceedings of the 22nd ACM international conference on Conference on information & knowledge management (CIKM '13)
By Liangjie Hong, Shuang-Hong Yang
Issue Date:October 2013
pp. 2559-2560
Online user engagement optimization is key to many Internet business. Several research areas are related to the concept of online user engagement optimization, including machine learning, data mining, information retrieval, recommender systems, online A/B ...
     
Pursuing insights about healthcare utilization via geocoded search queries
Found in: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval (SIGIR '13)
By Eric Horvitz, Ryen W. White, Shuang-Hong Yang
Issue Date:July 2013
pp. 993-996
Mobile devices provide people with a conduit to the rich infor-mation resources of the Web. With consent, the devices can also provide streams of information about search activity and location that can be used in population studies and real-time assistance...
     
Friend or frenemy?: predicting signed ties in social networks
Found in: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval (SIGIR '12)
By Alexander J. Smola, Bo Long, Hongyuan Zha, Shuang-Hong Yang, Yi Chang
Issue Date:August 2012
pp. 555-564
We study the problem of labeling the edges of a social network graph (e.g., acquaintance connections in Facebook) as either positive (i.e., trust, true friendship) or negative (i.e., distrust, possible frenemy) relations. Such signed relations provide much...
     
Functional matrix factorizations for cold-start recommendation
Found in: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information (SIGIR '11)
By Hongyuan Zha, Ke Zhou, Shuang-Hong Yang
Issue Date:July 2011
pp. 315-324
A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressively querying user responses through an initial interview process has been propose...
     
Collaborative competitive filtering: learning recommender using context of user choice
Found in: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information (SIGIR '11)
By Alexander J. Smola, Bo Long, Hongyuan Zha, Shuang-Hong Yang, Zhaohui Zheng
Issue Date:July 2011
pp. 295-304
While a user's preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learning recommender models. In particular, existing collaborative filtering (CF) appr...
     
Like like alike: joint friendship and interest propagation in social networks
Found in: Proceedings of the 20th international conference on World wide web (WWW '11)
By Alex Smola, Bo Long, Hongyuan Zha, Narayanan Sadagopan, Shuang-Hong Yang, Zhaohui Zheng
Issue Date:March 2011
pp. 537-546
Targeting interest to match a user with services (e.g. news, products, games, advertisements) and predicting friendship to build connections among users are two fundamental tasks for social network systems. In this paper, we show that the information conta...
     
Ranking with auxiliary data
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Bo Long, Shuang Hong Yang, Srinivas Vadrevu, Yi Chang, Zhaohui Zheng
Issue Date:October 2010
pp. 1489-1492
Learning to rank arises in many information retrieval applications, ranging from Web search engine, online advertising to recommendation system. In learning to rank, the performance of a ranking function heavily depends on the number of labeled examples in...
     
Language pyramid and multi-scale text analysis
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Hongyuan Zha, Shuang-Hong Yang
Issue Date:October 2010
pp. 639-648
The classical Bag-of-Word (BOW) model represents a document as a histogram of word occurrence, losing the spatial information that is invaluable for many text analysis tasks. In this paper, we present the Language Pyramid (LaP) model, which casts a documen...
     
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
Found in: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '09)
By Gu Xu, Hang Li, Shuang-Hong Yang
Issue Date:June 2009
pp. 1-24
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially useful in many applications including web search, online advertisement, and reco...
     
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