PAWS meeting - Feb 25, 2009

Comments on the first presentation here.

In the second part of the meeting Zhen presented her work about collaborative information behavior (CIB). She studied aspects of CIB by simulating e-discovery tasks and obtained some insights such as: Communication is frequent and an essential component of CIB; the division of labor is common in the collaborative task of e-discovery; and it is important for collaborators to keep “awareness” of each other’s activities to make sure the collaboration goes well. Based on these insights, some functions for retrieval systems that support CIB were proposed: Collaborative information retrieval technologies should support collaborative information behaviors including verbal communication and text exchanging. A well designed CIR system should support both synchronous collaboration and asynchronous collaboration.

[week 5] Muddiest Points

Talking about the Probability Ranking Principle, it was mentioned the case of retrieval costs but we didn't deepen into that concept. In the case that Costs are taking into account in a retrieval model:

• Which are commonly the values for these "C" costs?

• Which variables or factors are taking into account to set these costs values (hardware, size of collection, mean size of documents, etc)?

Another question I have is that several models take constants into account and after some experiments they suggest a range to set the values of those constants when defining a model. I am not absolutely sure, but these ranges must come using metrics such as precision and recall, and the documents collections must come from a programme like TREC. Is this enough to establish a model? It seems that all the theory for these probabilistic and language models is, in practice, oversimplified by smoothing factors and other constants added to the models. How can we be sure that the theory still states when adding these factors and constants in practice?

PAWS meeting - Feb 04, 2009

housekeeping things:
1. use tags to represent projects and systems in CiteULike. to keep our publications up-to-date. alternatively, update them on wiki.

Project 1: Personalized Exploratorium for Database Courses
Tag#1: DBExp
Tag#2: QuizGuide
Tag#3: WebEx
Tag#4: SQLKnoT
Tag#5: SQLTutor(If the paper is related to the system or Tanja is involved in the system)

Project 2: Adaptive Explanatory Visualization for Learning Programming Concepts
Tag#1: Adapvisual
Tag#2: cWADEIn
Tag#3: jWADEIn
Tag#4: Problets

Project 3: Supporting Learning from Examples in a Programming Course
Tag#1: ExampleSupport
Tag#2: NavEx
Tag#3: WebEx

Project 4: Map-Based Access to Open Corpus Information
Tag#1: MapAccess
Tag#2: KnowledgeSea2
Tag#3: KnowledgeSea

Project 5: Educational Software for Teaching and Learning Information Retrieval
Tag#1: EduSW

Project 6: Project 6: Individualized Exercises for Assessment and Self-Assessment of Programming Knowledge
Tag#1: IndExe
Tag#2: QuizPack
Tag#3: QuizGuide

Projects which are not listed in neither on Taler nor on Paws.
- QuizJet
- Proactive
- Pittcult (Even this is my personal project, you can decide whether this could be listed on Paws or not)

2.
produce slide presentation which includes good system screenshots.

3. Dhruba presented the workshop paper for IUI conference.
CiteAware: Visual Group Awareness for a Reference Sharing System
Awareness thru visualization removes the hierarchies.
Demo the system, CiteAware.