PAWS meeting 2008-12-02

Tailoring of feedback in online assessment: lessons learned [presented by Sharon]
- importance of system feedback to students, summary of 4 studies
- check feedback influence against learning styles (Kolbert)

PeerPigeon: a web applcation to support generalized peer review [presented by Sharon]
- peer review cycle (stages of review), peer review transforms (review items)
- several peer review patterns (conference style, journal style, etc.)
- RESTful design, ruby on rails

HeyStaks (presented by JaeWook)
- FireFox extension, overlay for Google search (tags, comments)
- Organize search activity as "staks"
- Share staks with peer users, receive staks, search items, tags from peers

PAWS Meeting 11/25/2008

In this session, Danielle and Jae-wook presented some papers from RecSys 2008, VAST 2008 and VIS 2008.

Danielle presented the paper “The long tail of recommender systems and how to leverage it”, in which the author’s aim is to improve recommendations using many items that are commonly in the long tail, because they have only few ratings (Danielle shows an example graph from MovieLens). The authors present and analyze three approaches: Each item method, Total Clustering method and Clustered Tail method.

Danielle also recommended reading the following papers:

• Integrating tags in a semantic content-based recommender

• Personalized recommendation in social tagging systems using hierarchical clustering

Jaek presented 3 papers:

• Entity-Based Collaboration Tools for Intelligence Analysis (VAST 2008): This paper presents a system called CorpusView. This system is based on entities and is intended for information analysis. Among different functionalities, it provides an entity workspace with a tool for collaboration, note taking, note sharing, collapsing information and recommendations through spreading activation.

• Visual Cluster Analysis of Trajectory Data with Interactive Kohonen Maps (VAST 2008): In this paper Jaek showed us a system aimed to make cluster analysis. The system combines clustering and specialization (Kohonen maps) showing trajectory data. It also integrates the work of experts in the automatic process to monitor and control by domain knowledge.

• Vectorized Radviz and Its Application to Multiple Datasets (VIS 2008): Radviz is a radial visualization with dimensions assigned to points called dimensional anchors (DAs) placed on the circumference of a circle. Records are assigned locations within the circle as a function of its relative attraction to each of the Das [taken from the abstract of the paper].
  

Blogger: Denis (Dalpasa)