HOME
ABOUT US
PRODUCTS
DOWNLOAD
PARTNERS
CONTACT US
LINKS
Company Overview
Management Team
Products
Frequently Asked Questions
Document Summary Systemâ„¢ - About Us - Biographies
(back)
Dr. Ye Shiren
Director of Research
yeshiren@clearlyunderstood.com
Tel: +(65) 6516.1181 Fax: +(65) 6779.1610
Dr. Ye Shiren was born in Changsha, Hunan, China and has the following education:
- Ph.D. Thesis in Research on Reducing and Classifying Massive Data
- Ph.D. in Computer Science from the
Institute of Computing Techology, Chinese Academy of Sciences
, 09/1998 - 06/2001
- Master in Computer Software from the
University of Xiangtan
, 09/1995 - 06/1998
- Bachelor in Engineering from the
University of Xiangtan
, 09/1988 - 06/1992
Research Interests:
- Data Miningand Machine Learning
- Intelligent Information System
- Text Mining and Information Extraction
- Natural Language Processing and Application
Systems:
-
Web Information Extraction and Extraction
-
smarTALK
-
Information Retrieval and Filtering System
-
Chinese Named Entity Identification System
-
MSMiner
-
Document Summary System for Selecting Fraudulent Taxation Cases (TaxDSS)
-
wiki
Publications:
-
Learning Object Models from Semi-Structured Web Documents
-
Clustering Web Pages about Persons and Organizations
-
NUS at DUC 2005: Understanding Documents via Concept Links, Document
-
Learning Object Model from Product Web Pages
-
Detecting and Partitioning of Data Objects in Complex Web Pages
-
Grouping Web Pages about Persons and Organizations for Information Extraction
- Learning Pattern Rules for Chinese Named-Entity Extraction<
- Tree's Drawing Algorithm and Visualizing Method
- Predicting Central Fishing Zone Based on CBR
- MSMiner: a Multi-strategy Data Mining Platform
- Machine Learning in KDD
- A Intelligent Navigator in Web-based Education
- Framework Representation in Reviewing Fishing Prediction
- General Multi-Strategy Data Mining Platform
- Lattice-based Multi-dimensional Data Analysis
- Fishing Resources Evaluation System
- Similarity Calculation in High-dimensional Data
- O-O Knowledge Processing in Cases Selection, J. of Computer App., Jan 1999