Staff

Speaker: Salvador Garcia-Martinez (McMaster University)

Through the development of Multi-Agent Systems, different architectures for agent systems have emerged. They follow different models and standards, but at the same time they share something in common: elements and relations. In this talk, I will discuss different multi-agent architectures that have been developed, focusing mainly on their similarities and how they have been implemented.

Speaker: Saeed Hassanpour

Recognition of cursive handwritings such as Persian script is a hard task as there is no fixed segmentation and simultaneous segmentation and recognition is required. We presents a novel comparison method for such tasks which is based on a Multiple States Machine to perform robust elastic comparison of small segments with high speed through generation and maintenance of a set of concurrent possible hypotheses.

Speaker: Jie Zhang

Familiarity between agents is often considered to be an important factor in determining the level of trust. In electronic marketplaces, trust is modeled, for instance, in order to allow buying agents to make effective selection of selling agents. In previous research, familiarity between two agents has been simply assumed to be the similarity between them, which is fixed for the two agents.

Speaker: Jiye Li

Clickstream data collected across multiple websites (user-centric data) captures users' browsing behaviors, interests and preferences more than clickstream data collected from individual websites (site-centric data). For example, we would expect that we could better model and predict the intentions of users who we know not only searched on google but also visited certain shopping websites, than if we know only one of these pieces of information. Current research on clickstream data analysis is mostly centered around site-centric data.

Speaker: Feng Jiao

We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data.

Speaker: David Hirtle

One explanation as to why the Semantic Web has not quite caught on yet is that the barrier to entry is too high. This talk describes TRANSLATOR, a free tool available as a Java Web Start application designed to allow anyone, even non-experts, to write facts and rules in formal representation for use on the Semantic Web.

Speaker: Fei Song (University of Guelph)

Text categorization is the process of assigning predefined categories to textual documents. As the exponential growth of web pages and online documents continues, there is an increasing need for systems that automatically classify text into proper categories.

Speaker: Shaheen Fatima

Sequential and simultaneous auctions are two important mechanisms for buying and selling multiple objects. These two mechanisms yield different outcomes (i.e., different surpluses, different revenues, and also different profits to the winning bidders). Given this, we compare the outcomes for the sequential and simultaneous mechanisms for the following scenario.

Speaker: David Tausky

In this talk, I will describe our prototype pen-based system for entering and manipulating mathematical expressions, currently called MathBrush.

Speaker: Mattt Enns

For my Masters thesis I researched the effects of word sense disambiguation on lexical chains. A lexical chain is a sequence of words in a document that are semantically related (i.e., related in meaning).