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Ph.D. Dissertation Defense

A Trust and Reputation Mechanism Through
Behavioral Modeling of Reviewers

Yasaman Haghpanah

11:00am Tuesday 21 August 2012, ITE 325b, UMBC

Trust and reputation have become important topics in various domains, such as online markets, supply chain management, auctions, social networks, and e-commerce applications. With the significant increase in transactions with people and organizations especially in online markets, people need to interact with strangers with whom they have little or no previous interactions. Reputation information as a form of world of mouth in auctions and supply chain management and as a form of provided reviews and ratings on online websites are two different sources for modeling trust and reputation in order to mitigate the risk of not knowing a stranger before actually start interacting with that stranger.

In providing reputation information, people can have different behavior, such as being biased based on incentives or they can have different preferences and viewpoints. In this dissertation, I introduce a novel trust and reputation mechanism that models and learns a reputation provider’s behavior based on probability theory. This learned behavior is then used to re-interpret the reputation information, thus making use of the entire reputation data effectively, even if they are biased or based on personal viewpoints and preferences.I show the importance of learning the behavior of reputation providers using different patterns of being biased or having different preferences and satisfaction thresholds in three different settings of game-theory, an online rating website, and an online marketplace. My results show that learning the behavior of reputation providers in all three above settings helps individuals to more effectively aggregate and adjust reputation information in order to make decisions, thereby increasing their satisfaction and overall payoffs in their interactions.

Committee: Drs. Marie desJardins (Chair), Tim Oates, Tim Finin, Wolfgang Ketter and David Aha

Congratulations to Xianshu Zhu (CS, Ph.D.), who won the best student paper award at the 13^th IEEE International Conference on Information Reuse and Integration.

The conference, which took place last weekend in Las Vegas, is a forum to discuss how we can maximize the reuse of information with the creation of simple, rich, and reusable knowledge representations.

Xianshu’s paper, “Finding Story Chain in Newswire Articles”, seeks to do just that through a proposed walk based algorithm that can be used to find news story chains on the internet. The algorithm sifts through the huge and hard to navigate database of news articles on the internet, resulting in a simple way to track the evolution of a news story, without redundant articles.

Xianshu’s areas of study include data mining, text mining, information retrieval. The paper is closely tied to the research she’s doing for her Ph.D. thesis (advised by Professor Tim Oates), which she plans on finishing up in May 2013.

PhD Dissertation Preliminary Examination

On Optimizing Contrast Quality and Acquisition Time of
SSFP-Sequence-Based techniques for Structural and Functional
MR Imaging via Extended Phase Graph (EPG) Analysis

Albert Kir

1:00pm Wednesday, 15 August 2012, ITE 325b

The extended phase graph (EPG) formalism provides an excellent description of the magnetization evolution (considering the magnetization as a vector quantity in space and its change through time) for steady-state free precession techniques (sequences). This dissertation demonstrates its accuracy by applying it to analyze/optimize structural and functional magnetic resonance imaging. An optimization framework for a structural imaging technique, Magnetization-Prepared RApid Gradient-Echo (MP-RAGE), based on the EPG algorithm is established for obtaining optimal images with respect to image signal strength, contrast, and acquisition time. In addition, a functional imaging technique, True Fast Imaging with Steady-state Precession (TruFISP) with improved quantitative sensitivity is developed using EPG analysis.

Committee: Drs. Joel M. Morris (chair and co-advisor), Alan McMillan (co-advisor), Rao Gullapalli (co-advosor), Janet Rutledge and Tulay Adali

The IEEE Baltimore Electron Devices Society chapter, in collaboration with ARL, will be hosting a one day Colloquium on Energy Harvesting Devices at the University of Maryland, College Park on Tuesday, September 25, 10 a.m. to 5 p.m. in the Stamp Student Union Building, Benjamin Banneker Room (Room 2212).

Invited speakers include:

Dr. Edward Shaffer, Army Research Laboratory
Prof. Vikram Dalal, Iowa State University
Prof. Santosh Kurinec, Rochester Institute of Technology
Dr. James Horwitz, Dept. of Energy (DOE)
Prof. Edward Yu, University of Texas,Austin
Prof. Rajendra Singh, Univ. of South Carolina
Prof. Agis IliadisUniv. of MD, College Park

Panel discussion on paths to reliable, efficient and low cost solar cell development (Dr. Anu Kaul/NSF, Chair, Dr. Mike Wraback ARL, Mr. Scott Stephens, DOE).

Attendance is free. To register, please contact: Dr. Naresh C. Das (Sorry, you need javascript to view this email address. ) or Dr. Victor Veliadis (Sorry, you need javascript to view this email address. )

For more information, visit the website and download the flyer.