Talks
Forthcoming talks
Past talks
Attribute Constrained Rules for Partially Labeled Sequence Completion
Where: Industrial Conference on Data Mining, Leipzig, Germany When: July 2009
LikeAttribute Constrained Rules: A New Approach to Missing Traveler Data
Where: University Of Illinois At Chicago Computer Science, Presented for the Computer Science Colloquium Series hosted by the IGERT Computational Transportation Science group When: July 2009
Sequential pattern and rule mining have been the focus of much research in the data mining community, however predicting missing sets of elements within a sequence remains a challenge. Recent work in survey design suggests that if these missing elements can be inferred with a higher degree of certainty, it would greatly reduce the time burden on survey participants. To address this problem and the more general problem of missing sensor data, we introduce a new form of constrained sequential rules that use attribute presence to better capture rule confidence in sequences with missing data than previous constraint based techniques. Specifically we examine the problem of given a partially labeled sequence of sets of attributes, how well can the missing attributes be inferred. Our study shows this technique significantly improves prediction robustness when even large amounts of sequence data are missing compared to traditional techniques, as demonstrated on a publicly available travel survey data set.
Keywords: Classification, prediction, association rules, pattern mining, sequential rules
Learning Travel Patterns of Individuals
Where: University Of Illinois At Chicago Computer Science, IGERT Seminar Series When: January 2009
Mining Sequential Association Rules for Traveler Context Prediction
Where: First International Workshop on Computational Transportation Science, Dublin, Ireland When: July 2008
Poster: Computational Transportation Science: An Interdisciplinary Approach to Integrating Emerging Technologies into Transportation
Where: NSF IGERT Project Meeting Dates: 18th May 2008 - 20th May 2008 When: May 2008
Co-authored with Ouri Wolfson and Peter C. Nelson
Recent advances in areas such as portable computing, wireless communications, and global positioning systems (GPS) offer significant opportunities for improving the overall travel experience. The potential applications from these technologies promise to revolutionize the way we connect with our environment and make travel decisions; however with this comes many technical challenges as well as privacy and security questions. Computational transportation science focuses on developing a scientific basis for incorporating emerging technologies in transportation related applications, and addressing issues associated with these advances. Research areas range from information management and communication systems that must scale and handle highly dynamic environments gracefully, to modeling traveler behavior and associated privacy issues. The goal of this work is to develop an experimental prototype, the Intelligent Traveler Assistant (ITA), to demonstrate the results of these various streams of research.
Quickly Learning Activity and Travel Patterns of Individuals: Transfer Learning for Individual Travel Behavior Prediction
Where: University Of Illinois At Chicago Computer Science, IGERT Seminar Series When: February 2008
Effective Attack Models for Shilling Item-Based Collaborative Filtering Systems
Where: WebKDD Workshop held at KDD 2005, Chicago, Illinois When: August 2005
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