Chun Jin
I am a post doctoral fellow at Language Technologies Institute, a unit of
School of Computer Science at Carnegie Mellon University.
My advisor is Professor
Jaime Carbonell.
I defended on Oct 31, 2006.
Curriculum vitae
Research
- ARGUS
I worked on profile matching with massive structured data.
- Topic Detection and Tracking
I worked on the First Story
Detection Task, and Topic Detection Task. See
NIST
site for more information on task definitions and evaluations.
- Summarization
Based on MMR framework, the summarizer summarizes
a long document or multiple documents into a short informative summary. It works
on English, Japanese, Chinese, and Spanish documents. It is also deployed
into a CMU TDT system.
- Is This Conversation on Track?
Sep. 2000 - Mar. 2001
A
project to improve confidence measure for the CMU Communicator
System.
- MAGIC
Apr. 1999 - Oct. 1999 Columbia University
I developed the tools to
extract features for speech synthesis.
Education
- Ph.D. October, 2006
Master of Science May, 2002
Language
Technologies Institute, School of
Computer Science, Carnegie Mellon
University
- Master of Science October, 1999
Dept. of Computer Science, Columbia University
- Master of Engineering April, 1996
- Bachelor of Engineering July, 1993
Dept. of
Computer Science, Xidian
University (Chinese Version)
Publications
-
Conference Papers
Red Opal: Product-Feature Scoring from Reviews
Christopher Scaffidi, Kevin Bierhoff, Eric Chang, Mikhael Felker, Herman Ng, and Chun Jin
Proceedings of the 8th ACM Conference on Electronic Commerce (EC), 2007
slides
ARGUS: Efficient Scable Continuous Query Optimization for Large-Volume Data Streams
Chun Jin and Jaime Carbonell
Proceedings of the Tenth International Database Engineering & Applications Symposium (IDEAS), 2006
Incremental Aggregation on Multiple Continuous Queries
Chun Jin and Jaime Carbonell
Proceedings of the 16th International Symposium on Methodologies for Intelligent Systems (ISMIS), 2006
ARGUS: Rete + DBMS = Efficient Persistent Profile Matching on Large-Volume Data Streams
Chun Jin, Jaime Carbonell, and Phil Hayes
Proceedings of the 15th International Symposium on Methodologies for Intelligent Systems (ISMIS), pages 142-151, 2005
Topic-conditioned Novelty Detection
Yiming Yang, Jian Zhang, Jaime Carbonell, and Chun Jin
Proceedings of ACM SIGKDD Internaltional Conference on Knowledge Discovery and Data Mining, pages 688-693, 2002
Is This Conversation on Track?
Carpenter P, Jin C, Wilson D,
Zhang R, Bohus D, Rudnicky A
Proceedings of EuroSpeech 2001,
pages 2121-2124
Technical Reports
ARGUS: Efficient Scalable Continuous Query Optimization for Large-Volume Data Streams
Chun Jin and Jaime Carbonell
Technical Report, CMU-LTI-06-005, Carnegie Mellon Univ. 2006
ARGUS: Rete + DBMS = Efficient Persistent Profile Matching on Large-Volume Data Streams
Chun Jin and Jaime Carbonell
Technical Report, CMU-LTI-04-181, Carnegie Mellon Univ. 2004
Posters
Scalable Data Exploration and Novelty Detection
J. Carbonell, E. Fink, C. Jin, C. Gazen, J. Mathew, A. Saxena, V. Satish, S. Ananthraman, D. Dietrich, G. Mani, J. Tittle, and P. Durbin
NIMD Grand Finale PI Meeting, Arlington, VA, April 2006
Exploring Massive Structured Data in ARGUS
Jaime Carbonell, Eugene Fink, Chun Jin, Cenk Gazen, Santosh Ananthraman, Phil Hayes, Ganesh Mani, and Dwight Dietrich
NIMD PI Meeting, Orlando, FL, November 2005
Approaches to Massive Structured Data in Argus
Jaime Carbonell, Phil Hayes, Eugene Fink, Chun Jin, and Cenk Gazen
NIMD PI Meeting, Orlando, FL, November 2004
Hypothesis Formation and Tracking in ARGUS
Cenk Gazen, Jaime Carbonell, Phil Hayes, Chun Jin, and Eugene Fink
NIMD PI Meeting, Orlando, FL, November 2004
Monitoring Large, Constantly Incrementing Collections of Structured Data for Complex Watch Patterns
Jaime Carbonell, Chun Jin, and Phil Hayes
NIMD PI Meeting, Crystal City, VA, May 2004
Finding Novel Information in Large, Constantly Incrementing Collections of Structured Data
Jaime Carbonell, Cenk Gazen, Chun Jin, Phil Hayes, Aaron Goldstein, Ganesh Mani, and Johny Mathew
NIMD PI Meeting, San Diego, CA, November 2003
Presentations
-
Finding Novel Patterns in Large, Constantly Incrementing Collections of Structured Data
by Santosh Ananthraman, Dwight Dietrich, Ganesh Mani, Abhay Saxena, Vini Satish, Chun Jin, and Eugene Fink
NIMD Grand Finale PI Meeting, April, 2006 (poster and demo)
Toward Incremental Sharing on Large-Scale Continuous Queries
Chun Jin
LTI Seminar, March 10, 2006 slides
Finding Novel Information in Large, Constantly Incrementing Collections of Structured Data
by Santosh Ananthraman, Phil Hayes, Ganesh Mani, and Chun Jin
NIMD PI Meeting, November, 2005 (poster)
Project ARGUS
Jaime Carbonell, Phil Hayes, Santosh Ananthraman, Chun Jin, Ganesh Mani, and Dwight Dietrich
ARDA NIMD Site Visit Report on ARGUS, Oct. 14, 2005
ARGUS: Rete + DBMS = Efficient Persistent Profile Matching on Large-Volume Data Streams
Chun Jin
LTI Seminar, April 22, 2005 slides
ARGUS: A Prototype Stream Anomaly Monitoring System
Chun Jin
Thesis Proposal, July 2004 slides
CMU TDT Report
Jaime Carbonell, Yiming Yang, Ralf Brown, Chun Jin, and Jian Zhang
TDT Workshop 2001 slides
Service
-
Member of Huaxia Chinese School (Marlboro Branch) PTA
Honor Certificate for Services
2003-2005
Student Volunteer of NAACL 2001
2001