Difference between revisions of "Hunt for Project partners"

Revision as of 21:18, 8 October 2012

Please add following details :

Name of project
a link to your project proposal(the same link that you put on http://malt.ml.cmu.edu/mw/index.php?title=List_of_project_proposals_for_10-802_in_Fall_2012)
contact person's email ID

Please remove the listing from this page, when you get desired number of team members. See following example :

project:Sample project
- Link prediction for the communication graphs including text
- Project description : I am interested in predicting links in the communication graph. But I am open to any link prediction tasks.
- Contact person : dummy@andrew.cmu.edu

project:Active Learning in Link Prediction for social networks
- Project description : Link prediction often works as a friend suggestion tool that users make confirmation to a list of friend suggestions provided by the system, which is similar to an active learning framework that the system can query the user by providing a suggestion and learn from the feedback. Please see the project page for details.
- Contact person : zhua@andrew.cmu.edu

project:Detection of Ad Hominem attacks in blog and review data
- Project description : I am interested in trying to automatically detect ad hominem and general person-directed insult in product reviews (for example, for a book written by Bill O'Reilly or Barack Obama, inciting verbal attacks against the author rather than the book content) and/or blog data (political blogs, or "hot-button" issue blogs). I have a manually curated training dataset of insult sentences, as well as scrapped blog data that can be mined. I'm open to working with one or two partners who can code in Python.
- Contact person : gmontane@andrew.cmu.edu

project:Adaptive Real-time Filtering in Twitter
- Project description: Given a topic, this project aims to filter an incoming tweet stream such that only tweets relevant to the topic are shown. It will follow the problem framework described in the Microblog Track of TREC 2012 and the goal of this project is to create and submit a competitive entry to the 2013 track (hint, publication, hint). Because the project involves modification of the Indri search engine, I'm looking for partners fluent in C++ (knowledge of a scripting language such as Python or Ruby is a plus). Also, since the submission for the conference opens in summer of 2013, it would be nice if you are willing to continue working on the project after the course to further improve it.
- Contact person : yubink@cmu.edu

Please add following details :

See following example :

Bhavana Dalvi (dummy@andrew.cmu.edu)
- wikipage:User:Bbd
- I am interested in doing a project related to viral marketing, also open to other ideas.

@@ Line 22: / Line 22: @@
 ** Project description :  I am interested in trying to automatically detect [http://en.wikipedia.org/wiki/Ad_hominem ad hominem] and general person-directed insult in product reviews (for example, for a book written by Bill O'Reilly or Barack Obama, inciting verbal attacks against the author rather than the book content) and/or blog data (political blogs, or "hot-button" issue blogs).  I have a manually curated training dataset of insult sentences, as well as scrapped blog data that can be mined. I'm open to working with one or two partners who can code in Python.
 ** Contact person : gmontane@andrew.cmu.edu
-*project:[[Catching and Forecasting Popular Videos on Youtube]]
-**Have you ever considered why some videos could attract millions of views within just a few days? Recently, research community begins to study the characteristics of the popular videos hoping the discovery would benefit the marketing and advertisement(YouTube Analysis). This project intents to model and predict the view pattern of popular videos with the emphasis on viral videos. Specially it involves the following tasks: dataset collection; the view growth distribution modeling based on BA model; popularity prediction by Naive method such as SVM or Regression.
-** Contact person : lujiang@cs.cmu.edu
 *project:[[Adaptive Real-time Filtering in Twitter]]