Chad A. Williams

Ph.D. candidate
Department of Computer Science
University of Illinois at Chicago

851 S. Morgan (M/C 152)
Chicago, IL  60607-7053

Ph:  630-881-4565
cwilliam    at   cs.uic.edu

About me
Teaching
CV (updated 10/29/2009)

Publications by date

Also see my publications by topic, by publication type, and by co-author.
Copyright notice.

2010

“Learning Activity Patterns of Individuals” (updated 10/29/2009)
by Chad A. Williams.
Ph.D. Dissertation, Department of Computer Science, University of Illinois at Chicago, expected Spring 2010.
Abstract +.

New! Urban Travel Route and Activity Choice Survey (UTRACS): An Internet-Based Prompted Recall Activity Travel Survey using GPS Data
by Martina Z. Frignani, Joshua Auld, Abolfazl Mohammadian, Chad Williams, and Peter Nelson.
In To appear in Proceedings of 89th Annual Meeting of the Transportation Research Board, (Washington D.C.), Jan. 2010.
Abstract +.

New! Urban Travel Route and Activity Choice Survey (UTRACS): An Internet-Based Prompted Recall Activity Travel Survey using GPS Data
by Martina Z. Frignani, Joshua Auld, Abolfazl Mohammadian, Chad Williams, and Peter Nelson.
tentatively accepted for publication in Transportation Research Record, Jan. 2010.
Abstract +.

2009

New! Attribute Constrained Rules For Partially Labeled Sequence Completion
by Chad A. Williams, Peter C. Nelson, and Abolfazl Mohammadian.
Advances in Data Mining - Applications and Theoretical Aspects, vol. 5633, July 2009, pp. 338 - 352.
Abstract +. Download: PDF.

An Automated GPS-Based Prompted Recall Survey With Learning Algorithms
by Joshua Auld, Chad A. Williams, Abolfazl Mohammadian, and Peter C. Nelson.
Transportation Letters: The International Journal of Transportation Research, vol. 1, no. 1, Jan. 2009, pp. 59-79.
Abstract +. Download: PDF.

2008

Mining Sequential Association Rules for Traveler Context Prediction
by Chad A. Williams, Abolfazl Mohammadian, Peter C. Nelson, and Sean T. Doherty.
In Proceedings of the First International Workshop on Computational Transportation Science, (Held at The International Conference on Mobile and Ubiquitous Systems: Networks and Services (MOBIQUITOUS 2008), Dublin, Ireland), July 2008.
Abstract +. Download: PDF.
A previous version appeared as “Mining Sequential Association Rules For Traveler Context Prediction” by Chad A. Williams, Abolfazl Mohammadian, Peter C. Nelson, and Sean T. Doherty. University of Illinois at Chicago Department of Computer Science Technical Report No. 2007.08.01-001 2007.08.01-001, Aug. 2007.

2007

Defending recommender systems: detection of profile injection attacks
by Chad Williams, Bamshad Mobasher, and Robin Burke.
Service Oriented Computing and Applications, vol. 1, no. 3, Nov. 2007, pp. 157-170.
Abstract +. Download: PDF.

Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness
by Bamshad Mobasher, Robin Burke, Runa Bhaumik, and Chad Williams.
ACM Transactions on Internet Technology, vol. 7, no. 4, Oct. 2007, ACM.
Abstract +. Download: PDF.

Genetically Evolving Optimal Neural Networks
by Chad Williams.
In Neural Networks and Expert Systems, Jan. 2007.
Abstract +. Download: PDF.

2006

Classification features for attack detection in collaborative recommender systems
by Robin Burke, Bamshad Mobasher, Chad Williams, and Runa Bhaumik.
In KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, (New York, NY, USA), 2006, pp. 542-547.
Abstract +. Download: PDF.

Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation
by B. Mobasher, R. Burke, C. Williams, and R. Bhaumik.
In Advances in Web Mining and Web Usage Analysis, vol. 4198 of Lecture Notes in Artificial Intelligence, (O. R. Zaïane O. Nasraoui and P. S. Yu, eds.), 2006, pp. 96-118.
Abstract +. Download: PDF.

The Impact of Attack Profile Classification on the Robustness of Collaborative Recommendation
by Chad Williams, Runa Bhaumik, Robin Burke, and Bamshad Mobasher.
In Proceedings of the 2006 WebKDD Workshop, (Held at KDD 2006, Philadelphia), Aug. 2006.
Abstract +. Download: PDF.

Detection of Obfuscated Attacks in Collaborative Recommender Systems
by Chad Williams, Bamshad Mobasher, Robin Burke, Jeff Sandvig, and Runa Bhaumik.
In Proceedings of the ECAI'06 Workshop on Recommender Systems, (Held at the 17th European Conference on Artificial Intelligence (ECAI'06), Riva del Garda, Italy), Aug. 2006.
Abstract +. Download: PDF.

Securing Collaborative Filtering Against Malicious Attacks Through Anomaly Detection
by Runa Bhaumik, Chad Williams, Bamshad Mobasher, and Robin Burke.
In Proceedings of the 4th Workshop on Intelligent Techniques for Web Personalization (ITWP'06), (Held at AAAI 2006, Boston, Massachusetts), July 2006.
Abstract +. Download: PDF.

Profile Injection Attack Detection for Securing Collaborative Recommender Systems
by Chad Williams.
Masters Thesis, Department of Computer Science, DePaul University, June 2006. Technical Report No. 06-014.
Abstract +. Download: PDF.

Detecting Profile Injection Attacks in Collaborative Recommender Systems
by Robin Burke, Bamshad Mobasher, Chad Williams, and Runa Bhaumik.
In Proceedings of the 8th IEEE Conference on E-Commerce Technology (CEC'06), (San Francisco, California), June 2006.
Abstract +. Download: PDF.

Evaluation of Profile Injection Attacks In Collaborative Recommender Systems
by Chad Williams, Runa Bhaumik, Jeff Sandvig, Bamshad Mobasher, and Robin Burke.
In DePaul CTI Research Symposium / Midwest Software Engineering Conference (CTIRS/MSEC 2006), (Chicago, Illinois), Apr. 2006.
Abstract +. Download: PDF.

2005

Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems
by R. Burke, B. Mobasher, R. Bhaumik, and C. Williams.
In Proceedings of the 2005 International Conference on Data Mining (ICDM'05), (Houston, Texas), Nov. 2005.
Abstract +. Download: PDF.

Collaborative Recommendation Vulnerability to Focused Bias Injection Attacks
by R. Burke, B. Mobasher, R. Bhaumik, and C. Williams.
In Proceedings of the Workshop on Privacy and Security Aspects of Data Mining, (Held at ICDM'05, Houston, Texas), Nov. 2005.
Abstract +. Download: PDF.

Effective Attack Models for Shilling Item-Based Collaborative Filtering Systems
by B. Mobasher, R. Burke, R. Bhaumik, and C. Williams.
In Proceedings of the 2005 WebKDD Workshop, (Held at KDD 2005, Chicago, Illinois), Aug. 2005.
Abstract +. Download: PDF.


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Chad Williams part of the UIC Computational Transportation Science group