Our group meets on Thursdays at 11:00 a.m., FL 246.
Dates and topics for this semester are as follows:
- Sept 9
- Organizational Meeting (Coordinator: Prof. Carolina Ruiz)
- Sept 16
- Joining the CS Theory Seminar:
Prof. Dan Dougherty
Graphs and the Semantic Web
In this talk I will discuss some recent results of Claudio Gutierrez, Carlos Hurtado, and Alberto Mendelzon, as presented in their paper "Foundations of Semantic Web Databases" by (Principles of Database Systems 2004).
- Sept 23
- Yoonsoo Kim
MS Thesis Presentation: Addressing the Data Recency Problem in Collaborative Filtering Systems
Recommender systems are being widely applied in many E-commerce sites to suggest products, services, and information items to potential users. Collaborative filtering systems, the most successful recommender system technology to date, help people make choices based on the opinions of other people. While collaborative filtering systems have been a substantial success, there are several problems that researchers and commercial applications have identified: the early rater problem, the sparsity problem, and the large scale problem. Moreover, existing collaborative filtering systems do not consider data recency. For this reason, if a user's preferences have changed over time, the systems might not recognize it quickly. This thesis studies how to apply data recency to collaborative filtering systems to get more predictive accuracy. We define the data recency problem as the negative impact of old data on the predictive accuracy of collaborative filtering systems. In order to mitigate this shortcoming, the combinations of time-based forgetting mechanisms, pruning and non-pruning strategies and linear and kernel functions, are utilized to apply weights. A clustering technique is employed to detect the user's changing preferences. We apply our research approach to the DeliBook dataset. The goal of our experiments is to show that our algorithm that incorporates temporal factors provides better recommendations than existing methods.
- Sept 30
- Prof. Carolina Ruiz
Research Projects in Knowledge Discovery and Data MiningIn this talk I will provide a brief tutorial-like introduction to the fields of knowledge discovery in databases and data mining as well as a description of some of the ongoing research projects at the WPI Knowledge Discovery in Databases and Data Mining Research Group (KDDRG).
- Oct 7
- Prof. Neil Heffernan
Research in Intelligent Tutoring Systems
- Oct 14
- Janet Elizabeth Burge
An Integrated Approach for Software Design Checking Using RationaleDesign Rationale (DR), the reasons behind decisions made while designing, offers a richer view of both the product and the decision-making process by providing the designer's intent behind the decisions. DR is also valuable for checking to ensure that the intent was adhered to throughout the design, as well as pointing out any unresolved (or undocumented) issues that remain open. While there is little doubt of the value of DR, it is typically not captured during design. SEURAT (Software Engineering Using RATionale) is a system we have developed to explore uses of design rationale. It supports both the display of and inferencing over the rationale to point out any unresolved issues or inconsistencies. SEURAT is tightly integrated with a software development environment so that rationale capture and use can become integrated into the software development process.
- Oct 21
- No meeting this day - Term break
- Oct 28
- Nov 4
- Nov 11
- Nov 18
- Aparna Varde
- Nov 25
- Thanksgiving Break
- Dec 2
- Dec 9
- Dec 16
- No meeting - Last day of the term/semester
email@example.com / Monday Oct 11 2004