Spatial and temporal context are increasingly important as users rely more on mobile devices to access information on the Web. Although information access applications are becoming more context-savvy, users' expectations are far ahead of current capabilities. For example, users expect a given application to understand the nature of their current immediate surroundings, while many systems have trouble drawing an accurate map of a city, or assigning a geographic and temporal scope to a web document. Successfully incorporating spatial and temporal context into the retrieval and user models for a system opens up a universe of hyperlocal scenarios.
Users provide an unprecedented volume of detailed, and continuously updated information about where they are, what they are doing, who they are with, and what they are thinking and feeling about their current activities. The provision of this stream creates an informal contract between the user and the information access application that the user will provide the information, but the application must provide results that are contextually relevant. Many of the research questions about how to understand and employ user context have yet to be answered.
In this workshop we explore spatial and temporal context in dynamic geotagged collections, such as Wikipedia, and traditional news sources, as well as social media sites such as Twitter, Foursquare, Facebook and Flickr. To ground the workshop, and provide a locus for discussion of the two aspects of user context, we focus on event detection and recommendation. Events are a natural theme around which to center discussions of spatial and temporal context because events are defined by their time and place. We aim to bring together practitioners and researchers to discuss their recent breakthroughs and the challenges with addressing spatial and temporal information access, both from the algorithmic and the architectural perspectives. This workshop would be a successor to the successful SIGIR 2012 and 2013 Workshops on Time Aware Information Access (#TAIA2012 & #TAIA2013). The 2012 edition was the first to bring together a broad set of academic and industrial researchers around the topic of time-aware information access. The specific focus of the 2013 workshop was on the many time-aware benchmarking activities in 2013. The focus this year will be spatial and temporal information, around the locus of event detection and recommendation.
- Submission Deadline: Monday, May 19th 2014 (23:59UTC-11; Samoa time zone)
- Acceptance Notifications: Monday, June 9th 2014
- Camera-ready Deadline: Friday, June 20th 2014
- Workshop: Friday, July 11th 2014
- Fernando Diaz (Microsoft)
- Claudia Hauff (Delft University of Technology)
- Vanessa Murdock (Microsoft)
- Maarten de Rijke (University of Amsterdam)
- Milad Shokouhi (Microsoft)
We plan a full day workshop, which will include 2-3 keynote speeches from a combination of industry and academia, and several talks of 20-30 minutes from accepted papers. We will publish a call for papers inviting submissions to the workshop. The workshop will be open to all registered SIGIR participants. The program will be accessible to people with a general IR background, who are new to spatial and temporal information access. At the same time, because the program centers around invited talks and a panel discussion, it will still be interesting for those who have already done significant work in related areas.
Call for Papers
We will welcome submissions related to all aspects of geographical and time-sensitive information access. TAIA 2014 will have a special focus on events, to include event detection, recommendation, and characterization. Research questions include:
- How can we detect events in social media?
- How can we best leverage our understanding of a user's location and time context to improve the ranking of places and content?
- How can we employ models of user generated content to describe places people visit?
- Can we construct a pro le of places of interest of users based on their social media streams?
- How can we detect and signal significant changes in such profiles?
- How can we model the footprint of a business from user social tagging behavior?
- How can we model the impact on a business based on users' online behavior?
In addition, TAIA 2014 welcomes contributions on the following issues that complement current technologies in spatial and temporal information:
- Publicly available dynamic collections (e.g. Wikipedia edits, Wikipedia page requests, Twitter and news streams).
- Evaluation methodologies for geo-constrained and time-sensitive tasks.
- Timeline creations and summarizations
- Spatial modeling of social media and Web content
- Spatial and temporal intent classification of queries
- Spatial and temporal natural language processing tasks and techniques
- Spatial and time-sensitive ranking, including, effective ranking for spatio-temporal context-sensitive queries, optimizing for both freshness and relevance, evaluating the results for context sensitive queries, etc.
- Temporal changes in document contents.
- Understanding Web dynamics, including trends and other temporal analysis on web and social graphs.
- Local search and recommendation.
The submissions will be peer reviewed (single-blind) and must be formatted according to the ACM SIG proceedings template with a maximum length of 4 pages. We welcome both position papers and reports on on-going research. Papers should be submitted online https://www.easychair.org/conferences/?conf=taia2014 by Monday, May 26th, 2014 (extended) 23:59UTC-11; Samoa time zone.
Acceptance notifications will be on Monday June 9th 2014.
- 09:00-09:15 Opening
- 09:15-10:00 Keynote I (Susan Dumais)
- 10:00-10:30 Break
- 10:30-11:15 Keynote II (James Caverlee)
- 11:15-12:15 Session I
- Shu Tang, Zhicheng Dou, Xing Xie and Jun He, "Detecting and Monitoring Dynamic Content Blocks of a Web Page by Merging its Historical Versions"
- Chandan Kumar, Wilko Heuten and Susanne Boll, "Event Based Characterization and Comparison of Geosocial Urban Environment"
- Danai Koutra, Paul Bennett and Eric Horvitz, "Influences of a Shocking News Event on Web Browsing"
- 11:55 13:30 Lunch
- 13:30-14:15 Keynote III (Miles Efron)
- 14:15-15:00 Discussion
- 15:00-15:30 Break
- 15:30-16:10 Session ||
- Arunav Mishra, Klaus Berberich and Dragan Milchevsk, "Linking Wikipedia Events to Past News"
- Nattiya Kanhabua and Wolfgang Nejdl, "On the Value of Temporal Anchor Texts in Wikipedia"
- 16:10-16:55 Discussion II
- 16:55-17:05 Closing
- Gianluca Demartini (University of Fribourg)
- Omar Alonso (Microsoft)
- Fabrizio Silvestri (ISTI - CNR)
- Nattiya Kanhabua (L3S Research Center)
- Pavel Serdyukov (Yandex)
- Thomas Mandl (University of Hildesheim)
- Filip Radlinski (Microsoft)
- Eytan Adar(University of Washington)
- Miles Efron(University of Illinois)
- Elad Yom-Tov (Microsoft Research)
- Benoit Huet (Eurecom)
- Brian Davison (Lehigh University)
Susan Dumais is a Distinguished Scientist at Microsoft and Deputy Managing Director of the Microsoft Research Lab in Redmond. She also manages the Context, Learning and User Experience for Search (CLUES) Group. Prior to joining Microsoft Research, she was at Bell Labs and Bellcore for many years, where she worked on Latent Semantic Analysis, techniques for integrating search and navigation, and organizational impacts of new technology. Her current research focuses on user modeling and personalization, temporal dynamics of information, context and search, and gaze-enhanced interaction techniques. She has worked closely with several Microsoft groups (Bing, Windows Desktop Search, SharePoint, and Office Online Help) on search-related innovations. Susan has published widely in the fields of information science, human-computer interaction and cognitive science, and holds several patents on novel retrieval algorithms and interfaces. Susan is an adjunct professor in the Information School at the University of Washington. She is Past-Chair of ACM's Special Interest Group in Information Retrieval (SIGIR), and serves on several editorial boards, technical program committees, and government panels. She was elected to the CHI Academy in 2005, an ACM Fellow in 2006, received the SIGIR Gerard Salton Award for Lifetime Achievement in 2009, was elected to the National Academy of Engineering (NAE) in 2011, and received the Athena Lecture Award in 2014. More information is available at her homepage.
James Caverlee is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University. His research focuses on web-scale information management, distributed data-intensive systems, and social computing. Most recently, he's been working on (i) spam and crowdturfing threats to social media and web systems; and (ii) geo-social systems that leverage large-scale spatio-temporal footprints in social media. Caverlee is a recipient of the 2010 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award, the 2012 Air Force Office of Scientific Research (AFOSR) Young Investigator Award, and a 2012 NSF CAREER Award. He received his Ph.D. from Georgia Tech in 2007, M.S. degrees in Computer Science (2001) and in Engineering-Economic Systems & Operations Research (2000) from Stanford University, and a B.A. in Economics from Duke University (1996, magna cum laude).
Miles Efron is an Associate Professor in the Graduate School of Library and Information Science at the University of Illinois, Urbana-Champaign, where he also holds a courtesy appointment in the Department of Computer Science. His research focuses on information retrieval, particularly in emerging domains such as social media and massive repositories of digitized books. He is currently working on information filtering problems, with special emphasis on applying unsupervised and semi-supervised statistical learning to filtering-related tasks. Miles received his Ph.D. from the University of North Carolina in 2003. He held a post-doc at UNC for a year following his doctoral work. He received an MSIS from the School of Information and Library Science at UNC in 2000 and a BA from Occidental College (summa cum laude) in 1994.