Graphics enhanced version of this site

Text Miner
Head: Katia Sycara
Contact: Lori R Price (lrprice@cs.cmu.edu)

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

For more information, see this project's homepage.

This page last updated - November 2005.

There is a positive correlation between news reports on a company's financial outlook and the company's attractiveness as an investment. However, because of the volume of such reports, it is impossible for financial analysts or investors to track and read all of them.

To address this problem, we have developed the Text Miner. Text Miner is a system that automatically classifies news reports that reflect positively or negatively on a company's financial outlook.

Name - Title <Email Address>
• [Home] Joseph Andrew Giampapa - Project Manager <garof@andrew.cmu.edu>
• [Home] Katia Sycara - Research Professor <katia@cs.cmu.edu>

Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.

• Installation, Running and Editing Instructions for the ClassificationBox Text Classification Tool
  M. Rectenwald, Y. Seo, K. Lee, J.A. Giampapa, and K. Sycara
  tech. report CMU-RI-TR-04-58, Robotics Institute, Carnegie Mellon University, November, 2004. [Abstract]
  Download: pdf [81 KB] copyrighted

• Proof of Concept System for Automatically Determining `Need-to-Know' Access Privileges: Installation Notes and User Guide
  M. Rectenwald, K. Lee, Y. Seo, J.A. Giampapa, and K. Sycara
  tech. report CMU-RI-TR-04-56, Robotics Institute, Carnegie Mellon University, October, 2004. [Abstract]
  Download: pdf [1151 KB] copyrighted

• Text Classification for Intelligent Portfolio Management
  Y. Seo, J.A. Giampapa, and K. Sycara
  tech. report CMU-RI-TR-02-14, Robotics Institute, Carnegie Mellon University, May, 2002. [Abstract]
  Download: pdf [110 KB], ps.gz [50 KB] copyrighted