Publication statistics

Pub. period:1992-2012
Pub. count:23
Number of co-authors:37


Number of publications with 3 favourite co-authors:

Robert Mao:
K. L. Mak:
Cindy Chen:



Productive colleagues

Wei Li's 3 most productive colleagues in number of publications:

W. Bruce Croft:124
Arie E. Kaufman:87
Tovi Grossman:44

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Wei Li


Publications by Wei Li (bibliography)

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Li, Wei, Grossman, Tovi and Fitzmaurice, George (2012): GamiCAD: a gamified tutorial system for first time AutoCad users. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 103-112.

We present GamiCAD, a gamified in-product, interactive tutorial system for first time AutoCAD users. We introduce a software event driven finite state machine to model a user's progress through a tutorial, which allows the system to provide real-time feedback and recognize success and failures. GamiCAD provides extensive real-time visual and audio feedback that has not been explored before in the context of software tutorials. We perform an empirical evaluation of GamiCAD, comparing it to an equivalent in-product tutorial system without the gamified components. In an evaluation, users using the gamified system reported higher subjective engagement levels and performed a set of testing tasks faster with a higher completion ratio.

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

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Karimzadehgan, Maryam, Li, Wei, Zhang, Ruofei and Mao, Jianchang (2011): A stochastic learning-to-rank algorithm and its application to contextual advertising. In: Proceedings of the 2011 International Conference on the World Wide Web 2011. pp. 377-386.

This paper is concerned with the problem of learning a model to rank objects (Web pages, ads and etc.). We propose a framework where the ranking model is both optimized and evaluated using the same information retrieval measures such as Normalized Discounted Cumulative Gain (NDCG) and Mean Average Precision (MAP). The main difficulty in direct optimization of NDCG and MAP is that these measures depend on the rank of objects and are not differentiable. Most learning-to-rank methods that attempt to optimize NDCG or MAP approximate such measures so that they can be differentiable. In this paper, we propose a simple yet effective stochastic optimization algorithm to directly minimize any loss function, which can be defined on NDCG or MAP for the learning-to-rank problem. The algorithm employs Simulated Annealing along with Simplex method for its parameter search and finds the global optimal parameters. Experiment results using NDCG-Annealing algorithm, an instance of the proposed algorithm, on LETOR benchmark data sets show that the proposed algorithm is both effective and stable when compared to the baselines provided in LETOR 3.0. In addition, we applied the algorithm for ranking ads in contextual advertising. Our method has shown to significantly improve relevance in offline evaluation and business metrics in online tests in a real large-scale advertising serving system. To scale our computations, we parallelize the algorithm in a MapReduce framework running on Hadoop.

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

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Li, Wei (2011): Domain-specific information retrieval using recommenders. In: Proceedings of the 34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2011. pp. 1327-1328.

The continuing increase in the volume of information available in our daily lives is creating ever greater challenges for people to find personally useful information. One approach used to addressing this problem is Personalized Information Retrieval (PIR). PIR systems collect a user's personal information from both implicit and explicit sources to build a user profile with the objective of giving retrieval results which better meet their individual user information needs than a standard Information Retrieval (IR) system. However, in many situations there may be no opportunity to learn about the specific interests of a user and build a personal model when this user is querying on a new topic, e.g. when a user visits a museum or exhibition which is unrelated to their normal search interests. Under this condition, the experiences and behaviours of other previous users, who have made similar queries, could be used to build a model of user behavior in this domain. My PhD proposes to focus on the development of new and innovative methods of domain-specific IR. My work seeks to combine recommender algorithms trained using previous search behaviours from different searchers with a standard ranked IR method to form a domain-specific IR model to improve the search effectiveness for a user entering a query without personal prior search history on this topic. The challenges for my work are: how to provide users better results; how to train and evaluate the methods proposed in my work.

© All rights reserved Li and/or ACM Press

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Li, Wei, Grossman, Tovi, Matejka, Justin and Fitzmaurice, George (2011): TwitApp: in-product micro-blogging for design sharing. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 185-194.

We describe TwitApp, an enhanced micro-blogging system integrated within AutoCAD for design sharing. TwitApp integrates rich content and still keeps the sharing transaction cost low. In TwitApp, tweets are organized by their project, and users can follow or unfollow each individual project. We introduce the concept of automatic tweet drafting and other novel features such as enhanced real-time search and integrated live video streaming. The TwitApp system leverages the existing Twitter micro-blogging system. We also contribute a study which provides insights on these concepts and associated designs, and demonstrates potential user excitement of such tools.

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

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Ekstrand, Michael, Li, Wei, Grossman, Tovi, Matejka, Justin and Fitzmaurice, George (2011): Searching for software learning resources using application context. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 195-204.

Users of complex software applications frequently need to consult documentation, tutorials, and support resources to learn how to use the software and further their understanding of its capabilities. Existing online help systems provide limited context awareness through "what's this?" and similar techniques. We examine the possibility of making more use of the user's current context in a particular application to provide useful help resources. We provide an analysis and taxonomy of various aspects of application context and how they may be used in retrieving software help artifacts with web browsers, present the design of a context-aware augmented web search system, and describe a prototype implementation and initial user study of this system. We conclude with a discussion of open issues and an agenda for further research.

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

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Li, Wei, Liu, Yaduo and Xue, Xiangyang (2010): Robust audio identification for MP3 popular music. In: Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2010. pp. 627-634.

Audio identification via fingerprint has been an active research field with wide applications for years. Many technical papers were published and commercial software systems were also employed. However, most of these previously reported methods work on the raw audio format in spite of the fact that nowadays compressed format audio, especially MP3 music, has grown into the dominant way to store on personal computers and transmit on the Internet. It would be interesting if a compressed unknown audio fragment is able to be directly recognized from the database without the fussy and time-consuming decompression-identification-recompression procedure. So far, very few algorithms run directly in the compressed domain for music information retrieval, and most of them take advantage of MDCT coefficients or derived energy type of features. As a first attempt, we propose in this paper utilizing compressed-domain spectral entropy as the audio feature to implement a novel audio fingerprinting algorithm. The compressed songs stored in a music database and the possibly distorted compressed query excerpts are first partially decompressed to obtain the MDCT coefficients as the intermediate result. Then by grouping granules into longer blocks, remapping the MDCT coefficients into 192 new frequency lines to unify the frequency distribution of long and short windows, and defining 9 new subbands which cover the main frequency bandwidth of popular songs in accordance with the scale-factor bands of short windows, we calculate the spectral entropy of all consecutive blocks and come to the final fingerprint sequence by means of magnitude relationship modeling. Experiments show that such fingerprints exhibit strong robustness against various audio signal distortions like recompression, noise interference, echo addition, equalization, band-pass filtering, pitch shifting, and slight time-scale modification etc. For 5s-long query examples which might be severely degraded, an average top-five retrieval precision rate of more than 90% can be obtained in our test data set composed of 1822 popular songs.

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Li, Wei, Liu, Yaduo and Xue, Xiangyang (2010): Robust music identification based on low-order Zernike moment in the compressed domain. In: Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2010. pp. 739-740.

In this paper, we devise a novel robust music identification algorithm utilizing compressed-domain audio Zernike moment adapted from image processing techniques as the pivotal feature. Audio fingerprint derived from this feature exhibits strong robustness against various audio signal distortions including the challenging pitch shifting and time-scale modification. Experiments show that in our test dataset composed of 1822 popular songs, a 5s music query example which might have been severely corrupted is still sufficient to identify its original near-duplicate copy, with more than 90% top five precision rate.

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

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Zhang, Dell, Mao, Robert and Li, Wei (2009): The recurrence dynamics of social tagging. In: Proceedings of the 2009 International Conference on the World Wide Web 2009. pp. 1205-1206.

How often do tags recur? How hard is predicting tag recurrence? What tags are likely to recur? We try to answer these questions by analysing the RSDC08 dataset, in both individual and collective settings. Our findings provide useful insights for the development of tag suggestion techniques etc.

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

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Matejka, Justin, Li, Wei, Grossman, Tovi and Fitzmaurice, George (2009): CommunityCommands: command recommendations for software applications. In: Proceedings of the ACM Symposium on User Interface Software and Technology 2009. pp. 193-202.

We explore the use of modern recommender system technology to address the problem of learning software applications. Before describing our new command recommender system, we first define relevant design considerations. We then discuss a 3 month user study we conducted with professional users to evaluate our algorithms which generated customized recommendations for each user. Analysis shows that our item-based collaborative filtering algorithm generates 2.1 times as many good suggestions as existing techniques. In addition we present a prototype user interface to ambiently present command recommendations to users, which has received promising initial user feedback.

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

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Mak, K. L. and Li, Wei (2008): Objective Evaluation of Seam Pucker Using an Adaptive Neuro-Fuzzy Inference System. In: Ranchordas, Alpesh and Arajo, Helder (eds.) VISAPP 2008 - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 2 January 22-25, 2008, Funchal, Portugal. pp. 234-239.

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Li, Yong-Wei, Li, Wei, Yu, Guo-Qing, Wang, Zhen-Yu and Guo, Peng (2007): Applied Research in Fuzzy Neural Network Predictive Control. In: Zhang, Du, Wang, Yingxu and Kinsner, Witold (eds.) Proceedings of the Six IEEE International Conference on Cognitive Informatics ICCI 2007 August 6-8, 2007, Lake Tahoe, CA, USA. pp. 408-410.

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Li, Wei and Chen, Cindy (2007): SQS - A Secure XML Querying System. In: Cordeiro, Jos and Filipe, Joaquim (eds.) ICEIS 2008 - Proceedings of the Tenth International Conference on Enterprise Information Systems Volume DISI June 12-16, 2007, Barcelona, Spain. pp. 413-416.

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Li, Wei, Zhang, Li, Huang, Darong and Zhang, Ying (2006): Research on the Reconstruction Technology of Diagnosis Sytstem Based on Immune Mechanism. In: Yao, Yiyu, Shi, Zhongzhi, Wang, Yingxu and Kinsner, Witold (eds.) Proceedings of the Firth IEEE International Conference on Cognitive Informatics ICCI 2006 July 17-19, 2006, Beijing, China. pp. 623-628.

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Li, Wei and Vaughn, Rayford B. (2006): Modeling and Simulating System Exploitations through Exploitation Graphs for Security Engineering. In: HICSS 2006 - 39th Hawaii International International Conference on Systems Science 4-7 January, 2006, Kauai, HI, USA. .

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Li, Wei and Allen, Edward B. (2005): An Access Control Model for Secure Cluster-Computing Environments. In: HICSS 2005 - 38th Hawaii International Conference on System Sciences 3-6 January, 2005, Big Island, HI, USA. .

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Rao, Wenbi and Li, Wei (2004): Design of An Open and Secure Ubiquitous Computing System. In: 2004 IEEE/WIC/ACM International Conference on Web Intelligence WI 2004 20-24 September, 2004, Beijing, China. pp. 656-659.

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Li, Wei and Kaufman, Arie E. (2003): Texture Partitioning and Packing for Accelerating Texture-Based Volume Rendering. In: Graphics Interface 2003 June 11-13, 2003, Halifax, Nova Scotia, Canada. pp. 81-88.

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Li, Wei, Wei, Xiaoming and Kaufman, Arie E. (2003): Implementing lattice Boltzmann computation on graphics hardware. In The Visual Computer, 19 (7) pp. 444-456.

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Li, Wei, Mueller, Klaus and Kaufman, Arie E. (2003): Empty Space Skipping and Occlusion Clipping for Texture-based Volume Rendering. In: Turk, Greg, Wijk, Jarke J. van and II, Robert J. Moorhead (eds.) 14th IEEE Visualization 2003 Conference VIS 2003 19-24 October, 2003, Seattle, WA, USA. pp. 317-324.

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Pinto, David, Branstein, Michael, Coleman, Ryan, Croft, W. Bruce, King, Matthew, Li, Wei and Wei, Xing (2002): QuASM: a system for question answering using semi-structured data. In: JCDL02: Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries 2002. pp. 46-55.

This paper describes a system for question answering using semi-structured metadata, QuASM (pronounced "chasm"). Question answering systems aim to improve search performance by providing users with specific answers, rather than having users scan retrieved documents for these answers. Our goal is to answer factual questions by exploiting the structure inherent in documents found on the World Wide Web (WWW). Based on this structure, documents are indexed into smaller units and associated with metadata. Transforming table cells into smaller units associated with metadata is an important part of this task. In addition, we report on work to improve question classification using language models. The domain used to develop this system is documents retrieved from a crawl of

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Wei, Xiaoming, Li, Wei, Mueller, Klaus and Kaufman, Arie E. (2002): Simulating Fire with Texture Splats. In: IEEE Visualization 2002 2002. .

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Li, Wei, Gauch, Susan, Gauch, John and Pua, Kok Meng (1996): VISION: A Digital Video Library. In: DL96: Proceedings of the 1st ACM International Conference on Digital Libraries 1996. pp. 19-27.

The goal of the VISION (Video Indexing for Searching Over Networks) project is to establish a comprehensive, online digital video library. We are developing automatic mechanisms to populate the library and provide content-based search and retrieval over computer networks. The salient feature of our approach is the integrated application of mature image or video processing, information retrieval, speech feature extraction and word-spotting technologies for efficient creation and exploration of the library materials. First, full-motion video is captured in real-time with flexible qualities to meet the requirements of library patrons connected via a wide range of network bandwidths. Then, the videos are automatically segmented into a number of logically meaningful video clips by our novel two-step algorithm based on video and audio contents. A closed caption decoder and/or word-spotter is being incorporated into the system to extract textual information to index the video clips by their contents. Finally, all information is stored in a full-text information retrieval system for content-based exploration of the library over networks of varying bandwidths.

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Cai, Shijie, Li, Wei and Zhang, Honggang (1992): A visual tool for user-interface development. In The Visual Computer, 8 (2) pp. 134-143. http://

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