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Sunday June 23, 2013Student Presenter

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Session 1Welcome & KeynoteWelcome from the Chairs

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09:00a - 10:30aChair: Cong YuKeynote: Badger: Toward Crowdsourcing the Building of Structured Knowledge Bases

AnHai Doan (University of Wisconsin)

Speaker Bio: AnHai Doan is an Associate Professor in the database group at the University of Wisconsin, Madison. His current interests include crowdsourcing, knowledge bases, social media, data integration, and information extraction. He received the ACM Doctoral Dissertation Award in 2003 and a Sloan fellowship in 2007. AnHai was Chief Scientist of Kosmix, a social media startup acquired by Walmart in 2011. Currently he also works as Chief Scientist of WalmartLabs, a research and development lab devoted to analyzing and integrating data for e-commerce. During his time at Wisconsin, Kosmix, and WalmartLabs, he has worked extensively on the problem of crowdsourcing the building of knowledge bases. He is also a co-author of “Principles of Data Integration” (with Alon Halevy and Zack Ives), a textbook published by Morgan Kaufmann in 2012.

Keynote Abstract:

Structured knowledge bases are becoming increasingly critical to a wide variety of semantic intensive applications, such as search, query understanding, question answering, e-commerce, social media analysis, entity matching, information extraction, and integration. Consequently, over the past decade numerous knowledge bases have been built, in both academia and industry. A general consensus is emerging that solving many "big data" problems require "big semantics", which often come in the form of big knowledge bases.

Today, however, there is no clear methodologies on how to build such knowledge bases. Most current ones have been built in a rather ad-hoc fashion, using a combination of algorithms and human effort, often in the form of crowdsourcing. While crowdsourcing is becoming increasingly critical, very little work has studied the problem. In response, we have recently started Badger, a joint project between the University of Wisconsin and WalmartLabs, to examine crowdsourcing for building knowledge bases. In this talk I will describe Badger, focusing on knowledge bases that we built at Wisconsin, Kosmix, and WalmartLabs, our effort to crowdsource them, the challenges that we ran into, lessons learned, and our current research directions. I will also introduce hands-off crowdsourcing, a novel form of crowdsourcing that potentially can allow any ordinary user to build structured knowledge bases.

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2-Minute Paper HighlightsStudent Presenter

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10:30a - 10:45aCoffee Break

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Session 2Structured Data10Enabling JSON Document Stores in Relational SystemsCraig Chasseur (University of Wisconsin); Yinan Li (University of Wisconsin); Jignesh Patel (University of Wisconsin)Craig

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10:45a - 12:15pChair: Oliver Kennedy26Containment for Tree Patterns with Attribute Value ComparisonsEvgeny Sherkhonov (University of Amsterdam); Maarten Marx (ISLA, University of Amsterdam)Evgeny

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30Simple Schemas for Unordered XMLIovka Boneva (University of Lille & INRIA, France ); Radu Ciucanu (Université Lille 1 & INRIA); Slawek Staworko (University of Lille & INRIA, France)Radu

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12:15p - 01:45pLunch (participant self-arrange)

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Session 3Knowledge Search25Mining Enterprise Websites for Association Thesaurus ConstructionLuciano Barbosa (AT&T Labs - Research)No

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01:45p - 03:15pChair: Pierre Senellart35Human-Powered Top-k ListsVassilis Polychronopoulos (UC Santa Cruz); Luca de Alfaro (UC Santa Cruz); James Davis (UC Santa Cruz); Hector Garcia-Molina (Stanford University); Neoklis Polyzotis (UC Santa Cruz)Vassilis

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43Enabling Author-Centric Ranking of Web ContentMuneeb Ali (Princeton University); Andrea LaPaugh (Princeton University)Muneeb

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03:15p - 03:30pCoffee Break

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Session 4Novel Applications34Monadic Logs for Collaborative Web ApplicationsSumit Agarwal (SUNY Buffalo); Daniel Bellinger (SUNY Buffalo); Oliver Kennedy (SUNY Buffalo); Ankur Upadhyay (SUNY Buffalo); Lukasz Ziarek (SUNY Buffalo)Ankur

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03:30p - 05:00pChair: Michael Gubanov36Fair Recommendations for Online Barter Exchange NetworksZeinab Abbassi (Columbia Univ); Laks Lakshmanan (University of British Columbia); Min Xie (University of British Columbia)Zeinab

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42Ringtail: Feature Selection For Easier NowcastingDolan Antenucci (University of Michigan); Michael Cafarella (University of Michigan); Margaret Levenstein (University of Michigan); Chris Re (University of Wisconsin); Matthew Shapiro (University of Michigan)Dolan

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05:00p - 05:10pChair: Cong YuAwards and Conclusion by the Chairs