Publication statistics

Pub. period:2001-2012
Pub. count:21
Number of co-authors:31


Number of publications with 3 favourite co-authors:

John Bodily:
Sandeep K. S. Gupta:
Bruno Lvy:



Productive colleagues

Bin Wang's 3 most productive colleagues in number of publications:

Wei-Ying Ma:95
Robert J. Kauffman:64
Gareth J. F. Jones:30

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Bin Wang


Publications by Bin Wang (bibliography)

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Fei, Yun, Wang, Bin and Chen, Jiating (2012): Point-tessellated voxelization. In: Proceedings of the 2012 Conference on Graphics Interface 2012. pp. 9-18.

Applications such as shape matching, visibility processing, rapid manufacturing, and 360 degree display usually require the generation of a voxel representation from a triangle mesh interactively or in real-time. In this paper, we describe a novel framework that uses the hardware tessellation support on the graphics processing unit (GPU) for surface voxelization. To generate gap-free voxelization results with superior performance, our framework uses three stages: triangle subdivision, point generation, and point injection. For even higher temporal efficiency we introduce PN-triangles and displacement mapping to voxelize meshes with rugged surfaces in high resolution. Our framework can be implemented with simple shader programming, making it readily applicable to a number of real-time applications where both development and runtime efficiencies are of concern.

© All rights reserved Fei et al. and/or their publisher

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Xu, Fei, Ji, Zongcheng and Wang, Bin (2012): Dual role model for question recommendation in community question answering. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 771-780.

Question recommendation that automatically recommends a new question to suitable users to answer is an appealing and challenging problem in the research area of Community Question Answering (CQA). Unlike in general recommender systems where a user has only a single role, each user in CQA can play two different roles (dual roles) simultaneously: as an asker and as an answerer. To the best of our knowledge, this paper is the first to systematically investigate the distinctions between the two roles and their different influences on the performance of question recommendation in CQA. Moreover, we propose a Dual Role Model (DRM) to model the dual roles of users effectively. With different independence assumptions, two variants of DRM are achieved. Finally, we present the DRM based approach to question recommendation which provides a mechanism for naturally integrating the user relation between the answerer and the asker with the content re-levance between the answerer and the question into a unified probabilistic framework. Experiments using a real-world data crawled from Yahoo! Answers show that: (1) there are evident distinctions between the two roles of users in CQA. Additionally, the answerer role is more effective than the asker role for modeling candidate users in question recommendation; (2) compared with baselines utilizing a single role or blended roles based methods, our DRM based approach consistently and significantly improves the performance of question recommendation, demonstrating that our approach can model the user in CQA more reasonably and precisely.

© All rights reserved Xu et al. and/or ACM Press

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Ma, Hongyuan and Wang, Bin (2012): User-aware caching and prefetching query results in web search engines. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 1163-1164.

Query results caching is an efficient technique for Web search engines. In this paper we present User-Aware Cache, a novel approach tailored for query results caching, that is based on user characteristics. We then use a trace of around 30 million queries to evaluate User-Aware Cache, as well as traditional methods and theoretical upper bounds. Experimental results show that this approach can achieve hit ratios better than state-of-the-art methods.

© All rights reserved Ma and Wang and/or ACM Press

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Xu, Yang, Jones, Gareth J. F. and Wang, Bin (2009): Query dependent pseudo-relevance feedback based on wikipedia. In: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2009. pp. 59-66.

Pseudo-relevance feedback (PRF) via query-expansion has been proven to be eective in many information retrieval (IR) tasks. In most existing work, the top-ranked documents from an initial search are assumed to be relevant and used for PRF. One problem with this approach is that one or more of the top retrieved documents may be non-relevant, which can introduce noise into the feedback process. Besides, existing methods generally do not take into account the significantly different types of queries that are often entered into an IR system. Intuitively, Wikipedia can be seen as a large, manually edited document collection which could be exploited to improve document retrieval effectiveness within PRF. It is not obvious how we might best utilize information from Wikipedia in PRF, and to date, the potential of Wikipedia for this task has been largely unexplored. In our work, we present a systematic exploration of the utilization of Wikipedia in PRF for query dependent expansion. Specifically, we classify TREC topics into three categories based on Wikipedia: 1) entity queries, 2) ambiguous queries, and 3) broader queries. We propose and study the effectiveness of three methods for expansion term selection, each modeling the Wikipedia based pseudo-relevance information from a different perspective. We incorporate the expansion terms into the original query and use language modeling IR to evaluate these methods. Experiments on four TREC test collections, including the large web collection GOV2, show that retrieval performance of each type of query can be improved. In addition, we demonstrate that the proposed method out-performs the baseline relevance model in terms of precision and robustness.

© All rights reserved Xu et al. and/or their publisher

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Xu, Yang, Ding, Fan and Wang, Bin (2008): Utilizing phrase based semantic information for term dependency. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 855-856.

Previous work on term dependency has not taken into account semantic information underlying query phrases. In this work, we study the impact of utilizing phrase based concepts for term dependency. We use Wikipedia to separate important and less important term dependencies, and treat them accordingly as features in a linear feature-based retrieval model. We compare our method with a Markov Random Field (MRF) model on four TREC document collections. Our experimental results show that utilizing phrase based concepts improves the retrieval effectiveness of term dependency, and reduces the size of the feature set to large extent.

© All rights reserved Xu et al. and/or ACM Press

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Xu, Yang, Ding, Fan and Wang, Bin (2008): Entity-based query reformulation using wikipedia. In: Shanahan, James G., Amer-Yahia, Sihem, Manolescu, Ioana, Zhang, Yi, Evans, David A., Kolcz, Aleksander, Choi, Key-Sun and Chowdhury, Abdur (eds.) Proceedings of the 17th ACM Conference on Information and Knowledge Management - CIKM 2008 October 26-30, 2008, Napa Valley, California, USA. pp. 1441-1442.

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Toledo, Rodrigo de, Wang, Bin and Lvy, Bruno (2008): Geometry Textures and Applications. In Comput. Graph. Forum, 27 (8) pp. 2053-2065.

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Lang, Hao, Wang, Bin, Jones, Gareth J. F., Li, Jintao and Xu, Yang (2008): An Evaluation and Analysis of Incorporating Term Dependency for Ad-Hoc Retrieval. In: Macdonald, Craig, Ounis, Iadh, Plachouras, Vassilis, Ruthven, Ian and White, Ryen W. (eds.) Advances in Information Retrieval - 30th European Conference on IR Research - ECIR 2008 March 30-April 3, 2008, Glasgow, UK. pp. 602-606.

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Guo, Ruijie, Cheng, Xueqi, Xu, Hongbo and Wang, Bin (2007): Efficient on-line index maintenance for dynamic text collections by using dynamic balancing tree. In: Silva, Mario J., Laender, Alberto H. F., Baeza-Yates, Ricardo A., McGuinness, Deborah L., Olstad, Bjrn, Olsen, ystein Haug and Falco, Andr O. (eds.) Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management - CIKM 2007 November 6-10, 2007, Lisbon, Portugal. pp. 751-760.

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Liu, Jing, Wang, Bin, Li, Mingjing, Li, Zhiwei, Ma, Wei-Ying, Lu, Hanqing and Ma, Songde (2007): Dual cross-media relevance model for image annotation. In: Lienhart, Rainer, Prasad, Anand R., Hanjalic, Alan, Choi, Sunghyun, Bailey, Brian P. and Sebe, Nicu (eds.) Proceedings of the 15th International Conference on Multimedia 2007 September 24-29, 2007, Augsburg, Germany. pp. 605-614.

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Kauffman, Robert J., Miller, Tim and Wang, Bin (2006): Reflections on: When Internet companies morph. In First Monday, 11 (0) .

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Li, Zhiwei, Wang, Bin, Li, Mingjing and Ma, Wei-Ying (2005): A probabilistic model for retrospective news event detection. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2005. pp. 106-113.

Retrospective news event detection (RED) is defined as the discovery of previously unidentified events in historical news corpus. Although both the contents and time information of news articles are helpful to RED, most researches focus on the utilization of the contents of news articles. Few research works have been carried out on finding better usages of time information. In this paper, we do some explorations on both directions based on the following two characteristics of news articles. On the one hand, news articles are always aroused by events; on the other hand, similar articles reporting the same event often redundantly appear on many news sources. The former hints a generative model of news articles, and the latter provides data enriched environments to perform RED. With consideration of these characteristics, we propose a probabilistic model to incorporate both content and time information in a unified framework. This model gives new representations of both news articles and news events. Furthermore, based on this approach, we build an interactive RED system, HISCOVERY, which provides additional functions to present events, Photo Story and Chronicle.

© All rights reserved Li et al. and/or ACM Press

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Tan, Songbo, Cheng, Xueqi, Wang, Bin, Xu, Hongbo, Ghanem, Moustafa M. and Guo, Yike (2005): Using dragpushing to refine centroid text classifiers. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2005. pp. 653-654.

We present a novel algorithm, DragPushing, for automatic text classification. Using a training data set, the algorithm first calculates the prototype vectors, or centroids, for each of the available document classes. Using misclassified examples, it then iteratively refines these centroids; by dragging the centroid of a correct class towards a misclassified example and in the same time pushing the centroid of an incorrect class away from the misclassified example. The algorithm is simple to implement and is computationally very efficient. Evaluation experiments conducted on two benchmark collections show that its classification accuracy is comparable to that of more complex methods, such as support vector machines (SVM).

© All rights reserved Tan et al. and/or ACM Press

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Tan, Songbo, Cheng, Xueqi, Ghanem, Moustafa, Wang, Bin and Xu, Hongbo (2005): A novel refinement approach for text categorization. In: Herzog, Otthein, Schek, Hans-Jorg and Fuhr, Norbert (eds.) Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management October 31 - November 5, 2005, Bremen, Germany. pp. 469-476.

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Banerjee, Sudipto, Kauffman, Robert J. and Wang, Bin (2005): A dynamic Bayesian analysis of the drivers of Internet firm survival. In: Li, Qi and Liang, Ting-Peng (eds.) Proceedings of the 7th International Conference on Electronic Commerce - ICEC 2005 August 15-17, 2005, Xian, China. pp. 151-158.

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Wang, Bin, Bodily, John and Gupta, Sandeep K. S. (2004): Supporting Persistent Social Groups in Ubiquitous Computing Environments Using Context-Aware Ephemeral Group Service. In: PerCom 2004 - Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications 14-17 March, 2004, Orlando, FL, USA. pp. 287-296.

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Kauffman, Robert J. and Wang, Bin (2003): Duration in the Digital Economy. In: HICSS 2003 2003. p. 227.

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Wang, Bin, Cheng, Xueqi and Bai, Shuo (2002): Example-based phrase translation in Chinese-English CLIR. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 435-436.

This paper proposes an example-based phrase translation method in a Chinese to English cross-language information retrieval (CLIR) system. The method can generate much more accurate query translations than dictionary-based and common MT-based methods, and then improves the retrieval performance of our CLIR system.

© All rights reserved Wang et al. and/or ACM Press

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Kauffman, Robert J., Miller, Tim and Wang, Bin (2002): When Internet Companies Morph: Understanding Organizational Strategy Changes in the 'New' New Economy. In First Monday, 7 (7) .

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Kauffman, Robert J., Wang, Bin and Miller, Tim (2002): Strategic 'Morphing' and the Survivability of E-commerce Firms. In: HICSS 2002 2002. p. 217.

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Kauffman, Robert J. and Wang, Bin (2001): New Buyers' Arrival under Dynamic Pricing Market Microstructure: The Case of Group-Buying Discounts on the Internet. In: HICSS 2001 2001. .

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