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Displaying 1-11 out of 11 total
MuSES: Multilingual Sentiment Elicitation System for Social Media Data
Found in: IEEE Intelligent Systems
By Yusheng Xie,Zhengzhang Chen,Kunpeng Zhang,Yu Cheng,Daniel K. Honbo,Ankit Agrawal,Alok N. Choudhary
Issue Date:July 2014
pp. 34-42
A multilingual sentiment identification system (MuSES) implements three different sentiment identification algorithms. The first algorithm augments previous compositional semantic rules by adding rules specific to social media. The second algorithm defines...
 
SES: Sentiment Elicitation System for Social Media Data
Found in: Data Mining Workshops, International Conference on
By Kunpeng Zhang,Yu Cheng,Yusheng Xie,Daniel Honbo,Ankit Agrawal,Diana Palsetia,Kathy Lee,Wei-keng Liao,Alok Choudhary
Issue Date:December 2011
pp. 129-136
Social Media is becoming major and popular technological platform that allows users discussing and sharing information. Information is generated and managed through either computer or mobile devices by one person and consumed by many other persons. Most of...
 
Learning to Group Web Text Incorporating Prior Information
Found in: Data Mining Workshops, International Conference on
By Yu Cheng,Kunpeng Zhang,Yusheng Xie,Ankit Agrawal,Wei-keng Liao,Alok Choudhary
Issue Date:December 2011
pp. 212-219
Clustering similar items for web text has become increasingly important in many Web and Information Retrieval applications. For several kinds of web text data, it is much easier to obtain some external information other than textual features which can be u...
 
SILVERBACK: Scalable association mining for temporal data in columnar probabilistic databases
Found in: 2014 IEEE 30th International Conference on Data Engineering (ICDE)
By Yusheng Xie,Diana Palsetia,Goce Trajcevski,Ankit Agrawal,Alok Choudhary
Issue Date:March 2014
pp. 1072-1083
We 1 address the problem of large scale probabilistic association rule mining and consider the trade-offs between accuracy of the mining results and quest of scalability on modest hardware infrastructure. We demonstrate how extensions and adaptations of re...
   
Random walk-based graphical sampling in unbalanced heterogeneous bipartite social graphs
Found in: Proceedings of the 22nd ACM international conference on Conference on information & knowledge management (CIKM '13)
By Ankit Agrawal, Lu Liu, Yusheng Xie, Alok Choudhary, Zhengzhang Chen
Issue Date:October 2013
pp. 1473-1476
We investigate sampling techniques in unbalanced heterogeneous bipartite graphs (UHBGs), which have wide applications in real world web-scale social networks. We propose random walked-based link sampling and stratified sampling for UHBGs and show that they...
     
On active learning in hierarchical classification
Found in: Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM '12)
By Alok Choudhary, Ankit Agrawal, Kunpeng Zhang, Yu Cheng, Yusheng Xie
Issue Date:October 2012
pp. 2467-2470
Most of the existing active learning algorithms assume all the category labels as independent or consider them in a "flat" structure. However, in reality, there are many applications in which the set of possible labels are often organized in a hierarchical...
     
Probabilistic macro behavioral targeting
Found in: Proceedings of the 2012 workshop on Data-driven user behavioral modelling and mining from social media (DUBMMSM '12)
By Alok Choudhary, Ankit Agrawal, Daniel Honbo, Jiangtao Gou, Kunpeng Zhang, Yi Gao, Yu Cheng, Yusheng Xie
Issue Date:October 2012
pp. 7-10
We investigate a class of emerging online marketing challenges in social networks; and formally, we define macro behavioral targeting (MBT) to be the marketing efforts that appeal to a massive targeted population with non-personalized broadcasting. Upon th...
     
CluChunk: clustering large scale user-generated content incorporating chunklet information
Found in: Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (BigMine '12)
By Alok Choudhary, Ankit Agrawal, Kunpeng Zhang, Yu Cheng, Yusheng Xie
Issue Date:August 2012
pp. 12-19
The exponential rise of online content in the form of blogs, microblogs, forums, and multimedia sharing sites has raised an urgent demand for efficient and high-quality text clustering algorithms for fast navigation and browsing of users based on better do...
     
Sentiment identification by incorporating syntax, semantics and context information
Found in: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval (SIGIR '12)
By Alok Choudhary, Ankit Agrawal, Daniel Honbo, Doug Downey, Kunpeng Zhang, Wei-keng Liao, Yu Cheng, Yusheng Xie
Issue Date:August 2012
pp. 1143-1144
This paper proposes a method based on conditional random fields to incorporate sentence structure (syntax and semantics) and context information to identify sentiments of sentences within a document. It also proposes and evaluates two different active lear...
     
Crowdsourcing recommendations from social sentiment
Found in: Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM '12)
By Alok Choudhary, Ankit Agrawal, Daniel Honbo, Kunpeng Zhang, Yu Cheng, Yusheng Xie
Issue Date:August 2012
pp. 1-8
In this paper, we investigate an innovative recommendation system by incorporating relevant social opinion and sentiment information. Our recommendation system, a powerful application of social sentiment analysis, differs from many existing models, which i...
     
VOXSUP: a social engagement framework
Found in: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '12)
By Alok Choudhary, Ankit Agrawal, Daniel Honbo, Kunpeng Zhang, Yu Cheng, Yusheng Xie
Issue Date:August 2012
pp. 1556-1559
Social media websites are currently central hubs on the Internet. Major online social media platforms are not only places for individual users to socialize but are increasingly more important as channels for companies to advertise, public figures to engage...
     
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