Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
20
click to vote
WEBI
2007
Springer
favorite
Email
discuss
report
104
views
Internet Technology
»
more
WEBI 2007
»
Mining Fuzzy Domain Ontology from Textual Databases
14 years 5 months ago
Download
eprints.qut.edu.au
Raymond Y. K. Lau, Yuefeng Li, Yue Xu
Real-time Traffic
Internet Technology
|
WEBI 2007
|
claim paper
Related Content
»
A semantic framework for personalized ad recommendation based on advanced textual analysis
»
Mining Fuzzy Rules in A Donor Database for Direct Marketing by a Charitable Organization
»
Casebased Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity
»
Using domain ontology for semantic web usage mining and next page prediction
»
Mining protein function from text using termbased support vector machines
»
Automated Generalization of Fuzzy Concept Hierarchies for AttributeOriented Induction Purp...
»
Flexible SPARQL Querying of Web Data Tables Driven by an Ontology
»
CPCV concept similarity mining without frequency information from domain describing taxono...
»
Discovering gene annotations in biomedical text databases
more »
Post Info
More Details (n/a)
Added
09 Jun 2010
Updated
09 Jun 2010
Type
Conference
Year
2007
Where
WEBI
Authors
Raymond Y. K. Lau, Yuefeng Li, Yue Xu
Comments
(0)
Researcher Info
Internet Technology Study Group
Computer Vision