There are four workshops hosted at WSDM 2015, covering novel topics and emerging areas in web search and data mining.

The workshops will be held on Feb 6. Please look at the websites of individual workshops for detailed information.


HIA’15: Heterogeneous Information Access Workshop at WSDM 2015

Information access is becoming increasingly heterogeneous. Especially when the user’s information need is for exploratory purpose, returning a set of diverse results from different re-sources could benefit the user. Aggregated search and composite retrieval are two instances of this new heterogeneous information access paradigm. Compared with traditional homogeneous search, optimization and evaluation in the context of heterogeneous information is more challenging and requires taking into account more complex user behaviors and interactions. We would like to create a forum to encourage discussion and exchange of ideas on heterogeneous information access in different contexts. To facilitate the discussion, we encourage submissions on ideas and results from different aspects of heterogeneous information access including aggregated search, composite retrieval, personal search, structured search, etc. Another objective of the workshop is to encourage submissions with novel ideas (e.g. new applications) on heterogeneous information access and potential future directions of this area.

Ke Zhou (Yahoo Labs London) is a research scientist working in Yahoo Labs London. He was previously a research associate in Language Technology Group in University of Edinburgh working on text mining and information retrieval. He has conducted his PhD research on evaluation of aggregated search at the Information Retrieval Group in University of Glasgow. He has published in reputable conferences (SIGIR, WWW, CIKM) and served as PC member for SIGIR, CIKM, ECIR, DL and AIRS. He also served as a co-organizer for NTCIR-11 IMine task and TREC FedWeb 2014 task.
Roger Jie Luo (Yahoo Labs Sunnyvale) is a Research Scientist and an engineering & science lead at Yahoo! Labs. At Yahoo!, he lead the efforts to improve the ranking of aggregated search results on the Yahoo! search result page and on understanding the users’ intents given a query. He obtained his PhD in computer science on machine learning from Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland.
Djoerd Hiemstra (University of Twente) is associate professor search engine and database technology at the University of Twente. He wrote an often cited PhD thesis on the use of statistical language models for information retrieval. His research interests include information retrieval, natural language processing and probabilistic graphical models. He co-authored over 200 research papers. Djoerd co-organized several workshops and conferences including SIGIR 2007, several editions of the Dutch-Belgian Information Retrieval Workshop (DIR), the SIGIR 2010 workshop on Accessible search and the ECIR 2013 workshop on Group membership and search.
Joemon Jose (University of Glasgow) is a full Professor at the School of Computing Science, University of Glasgow. He is a fellow of the BCS, IET and a chartered information technology professional (CITP), member of the and IEEE. He has a well-established reputation in research on multimedia information retrieval, developing advanced retrieval models, studying the role of emotion in search, personalization and adaptive retrieval. He has published over 150 journal and conference articles and leads a team of 9 PhD students and 2 post-doctoral researchers. He successfully, as local coordinator, completed 4 major EU funded projects on multimedia retrieval and multi-modal interaction (SALERO, MIAUCE, SEMEDIA, K-SPACE) and now participates in the LiMOSiNe project. He has organised number of information retrieval related events like ICMR 2014, ECDL 2010, workshops at previous SIGIR conferences, IR Fest in Glasgow 2005 etc. He has been senior PC member of the SIGIR, CIKM, ECIR conferences.


DL-WSDM’15: Workshop on Deep Learning for Web Search and Data Mining

Deep learning has been a very hot topic in the machine learning community. It has brought break-through results in image classification and speech recognition. Most recently, researchers have also got many promising results in natural language processing using deep learning techniques. As machine learning techniques are widely used in the Web search and data mining applications, many researchers and practitioners are studying the possibility of applying the recently-developed deep learning techniques into these applications. Some of them have made very promising progress, and thus it is a good time to hold a workshop to discuss and share the problems and progress in using deep learning techniques to improve Web search and data mining tasks. The main objective and goal of this workshop is to bring together researchers and practitioners that are applying machine learning (especially deep learning) techniques in Web search and data mining tasks, and enable them to share their latest research results, to express their opinions, and to discuss future directions. We expect that the WSDM audience get more familiar with the progress of deep learning and get more willing to try deep learning techniques in their research or application problems.

Taifeng Wang is a researcher in Artificial Intelligence group, Microsoft Research Asia. He has been working on internet advertising since Sep, 2010. His research focuses on modeling users’ behavior in ads system and help the search engine deliver better ads. The research topics include ads click prediction, user behavior targetting, ads optimization etc. He is also interested in machine learning, data mining and HCI design. Before working on ads, he has developed a large scale graph learning platform (codename: Graphor) which is going to handle learning and mining tasks on graphs with billions of node. He has worked on the Graphor project for three years. He has got several papers published on large scale graph learning, as long as several US patents filed regarding to distributed system. He joined MSRA in July 2006. He got his Master(2006) degree and BS(2003) degree in Electronic Engineering from University of Science and Technology of China. He has been with MSRA as a research intern from Mar. 2005 to Jan. 2006. During his internship, he worked on news search and text mining related topics.
Bin Gao is a lead researcher in Microsoft Research Asia. His research interests include machine learning, data mining, information retrieval, and computational advertising. He has authored two book chapters, 30 papers in top conferences and journals, and over 20 granted or pending patents. He co-authored the best student paper at SIGIR (2008). He serves as PC for SIGIR (2009~2014), WWW (2011~2013), and senior PC for CIKM (2011). He is a reviewer for TKDE, TIST, PRL, IRJ, TOIS, etc. He is a tutorial speaker at WWW (2011) and SIGIR (2012). He is a workshop organizer at ICDM (2012), SIGIR (2013), KDD (2013), and ICML (2014).
Jiang Bian is a researcher in Microsoft Research Asia, and his current research focuses on machine learning, data mining, and computational advertising. Before joining Microsoft, he worked at Yahoo! Labs and did many studies on content optimization and personalization for Yahoo!’s key content modules as well as local content search and recommendation for Yahoo!’s local services. Jiang received his B.S. from Peking University (2006) and Ph.D. from Georgia Institute of Technology (2010), both in Computer Science. He authored tens of academic research papers receiving hundreds of citations, filed a couple of U.S. patents, and served as PC member for a few international conferences, such as WWW, KDD, SIGIR, AAAI, IJCAI, CIKM, etc. He played as local co-chair for CIKM 2013. And, he also served as peer reviewer for a few journals, including TOIS, TIST, TKDE, JMLR, etc.


The 2nd workshop on Vertical Search Relevance at WSDM 2015

As the web information exponentially grows and the needs of users become more specific, traditional general web search engines are not able to perfectly satisfy the nowadays user requirement. Vertical search engines have emerged in various domains, which more focus on specific segments of online content, including local, shopping, medical information, travel search, etc. Vertical search engines start attracting more attention while relevance ranking in different vertical search engines is becoming the key technology. In addition, vertical search results are often slotted into general Web search results. Hence, designing effective ranking functions for vertical search has become practically important to improve users’ experience in both web search and vertical search. The workshop bring together researchers from IR, ML, NLP, and other areas of computer and information science, who are working on or interested in this area. It provides a forum for the researchers to identify the issues and the challenges, to share their latest research results, to express a diverse range of opinions about this topic, and to discuss future directions.

Dawei Yin is a research scientist at Yahoo Labs, working on search relevance issues, including mining the large corpora of click log and query logs, designing and developing better ways to understand query intent and improving search relevance. He has published more than 20 papers in premium conferences, such as KDD, SIGIR, WSDM, AAAI, etc. Before joining Yahoo labs, he obtained his Ph.D. degree from Lehigh University.
Oshin Hung received the MS degree from National Chiao Tung University (NCTU), Taiwan in 2005 and the Ph.D. degree in the Department of Computer Science from National Chiao Tung University, Taiwan, in 2011. Currently, he has already published 10 international conference papers and 4 international journal papers; especially, he received the Best Paper Award in Workshop on Location-Based Social Network in 2009. During his PhD program, he was a research intern in Microsoft Research Asia, Beijing, China. After getting the PhD degree, he served as a backend engineer in Global Media Foundation, and a research engineer in E-Commerce Department at Yahoo! Taiwan Ltd. Currently, he is a data scientist in Analyzing and Optimization Group, Big Data Department at Rakuten Inc., Japan.
Rui Li is a research scientist at Yahoo Labs, working on integrating various vertical results into web search results. His research interests include data mining, information retrieval and database system. He has published about 20 research papers in ICDE, VLDB, KDD, WWW, and SIGIR conferences. Before joining Yahoo labs, he obtained his PhD in the Data and Information Systems (DAIS) Lab at UIUC in 2013. He received his Bacholer’s degree from Shanghai Jiaotong University, China in 2007.
workshop-yi Yi Chang is a research director in Yahoo Labs in Sunnyvale, California. His research interests include Web search, applied machine learning, natural language processing and social computing. Yi has successfully organized the following workshops: Learning to Rank Workshop on ICML 2010; Transfer Learning Workshop on KDD 2012; Big Data on E-Commerce Workshop at PAKDD 2014; Vertical Search Relevance Workshop on WWW 2014.


WSDM’15 Workshop Summary / Scalable Data Analytics: Theory and Applications

With the fast evolving technology for data collection, data transmission, and data analysis, the scientific, biomedical, and engineering research communities are undergoing a profound transformation where discoveries and innovations increasingly rely on massive amounts of data. New prediction techniques, including novel statistical, mathematical, and modeling techniques are enabling a paradigm shift in scientific and biomedical investigation. Data become the fourth pillar of science and engineering, offering complementary insights in addition to theory, experiments, and computer simulation. Advances in machine learning, data mining, and visualization are enabling new ways of extracting useful information from massive data sets. The characteristics of volume, velocity, variety and veracity bring challenges to current data analytics techniques. It is desirable to scale up data analytics techniques for modeling and analyzing big data from various domains. The workshop aims to provide professionals, researchers, and technologists with a single forum where they can discuss and share the state-of-the-art theories and applications of scalable data analytics technologies.

Kaizhu Huang is currently an Associate Professor in Xian Jiaotong-Liverpool University and Director of Multimedia Telecommunications. Kaizhu Huang has been working in machine learning, pattern recognition, and neural information processing. He is the recipient of 2011 Asian Pacific Neural Network Assembly (APNNA) Distinguished Younger Researcher Award. He also received Best Book Award in National Three 100 Competition 2009. He has published 3 books in Springer and about 90 international research papers (28 SCI-indexed international journals and 50+ EI conference papers) e.g., in journals (JMLR, Neural Computation, IEEE T-PAMI, IEEE T-NN, IEEE T-BME, IEEE T-SMC, NN) and conferences (NIPS, IJCAI, SIGIR, UAI,CIKM, ICDM, ICML,ECML, CVPR). He serves as Advisory Board Member in Springer Book Series Bio-Neuroinformatics. He is the member of CCF Technical Committee of Artificial Intelligence and Pattern Recognition. He served on the program committees in many international conferences such as ICONIP, IJCNN, IWACI, EANN, KDIR. Especially, he serves as chairs in several major conferences or workshops, e.g., ICONIP 2014 (Program co-Chair), DMC 2012-2014 (Organizing co-Chair), ICDAR 2011 (Publication Chair), ACPR 2011 (Publicity Chair), ICONIP2006, 2009-2011 (Session Chair).
Haiqin Yang’s research interests include machine learning, data mining, and financial engineering. In these areas, he has over 30 technical publications in journals (JMLR, IEEE TNN, Neurocomputing, IEEE BME, IEEE SMC) and conferences (ICML, CIKM, IJCNN, ICONIP, etc.). In addition, he has written two books, four book chapters, and granted seven patents. He has served as a reviewer for many journals and in program committees for many conferences, e.g., CIKM, and IEEE BigData 2013, IEEE BDSE 2013. He also received many awards, including the “First Prize” postgraduate paper award in the IEEE Hong Kong Section 2010, PCCW Foundation Scholarship, and The Global Scholarship Program for Research Excellence. Dr. Yang is currently a Postdoctoral Fellow in The Chinese University of Hong Kong. He received his B.S. degree in the Computer Science and Technology in Nanjing University, his M.Phil. and Ph.D. degree in Computer Science and Engineering from The Chinese University of Hong Kong.
Irwin King is an associate dean of engineering faculty and a professor at the Department of Computer Science and Engineering, The Chinese University of Hong Kong. Prof. King’s research interests include machine learning, social computing, web intelligence, data mining, and multimedia information processing. In these research areas, he has over 210 technical publications in journals and conferences. In addition, he has contributed over 20 book chapters and edited volumes. Moreover, Prof. King has over 30 research and applied grants. One notable patented system he has developed is the VeriGuide System, previously known as the CUPIDE (Chinese University Plagiarism IDentification Engine) system, which detects similar sentences and performs readability analysis of text-based documents in both English and in Chinese to promote academic integrity and honesty.
Michael R. Lyu is currently a Professor in the Computer Science and Engineering department of the Chinese University of Hong Kong. Prof. Lyu’s research interests include software reliability engineering, distributed systems, fault-tolerant computing, web technologies, mobile networks, digital video library, multimedia processing, and video searching and delivery. He has participated in more than 30 industrial projects in these areas, and helped to develop many commercial systems and software tools. Prof. Lyu has published over 400 refereed journal and conference papers in his research areas. He initiated the first International Symposium on Software Reliability Engineering (ISSRE) in 1990. He was the Program Chair for ISSRE’96, Program co-Chair for WWW10, General Chair for ISSRE’2001, General co-Chair for PRDC’2005, and has served in program committees for many conferences. He was elected to IEEE Fellow (2004) and AAAS Fellow (2007) for his contributions to software reliability engineering and software fault tolerance. He was also named Croucher Senior Research Fellow in 2008 and IEEE Reliability Society Engineer of the Year in 2010.

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