Related references
Note: Only part of the references are listed.A process of knowledge discovery from web log data: Systematization and critical review
Zidrina Pabarskaite et al.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS (2007)
Classifying web documents in a hierarchy of categories: a comprehensive study
Michelangelo Ceci et al.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS (2007)
10 Challenging problems in data mining research
Qiang Yang et al.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING (2006)
Algorithmic computation and approximation of semantic similarity
Ana G. Maguitman et al.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2006)
Mining user access patterns with traversal constraint for predicting web page requests
Mei-Ling Shyu et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2006)
Mining web browsing patterns for E-commerce
Qinbao Song et al.
COMPUTERS IN INDUSTRY (2006)
Adaptive web information extraction - The Amorphic system works to extract Web information for use in business intelligence applications.
DG Gregg et al.
COMMUNICATIONS OF THE ACM (2006)
A web-page recommender system via a data mining framework and the Semantic Web concept
Choochart Haruechaiyasak et al.
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY (2006)
Mining user preferences, page content and usage to personalize website navigation
S Flesca et al.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2005)
Organizing information on the next generation web - Design and implementation of a new bookmark structure
SU Guan et al.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING (2005)
Mining web log sequential patterns with position coded pre-order linked WAP-tree
CI Ezeife et al.
DATA MINING AND KNOWLEDGE DISCOVERY (2005)
Optimizing the execution time for checking the consistency of XML documents
Y Kotb et al.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS (2004)
Learning rules for conceptual structure on theWeb
H Han et al.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS (2004)
Mining navigation patterns using a sequence alignment method
B Hay et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2004)
Collective mining of Bayesian networks from distributed heterogeneous data
R Chen et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2004)
Building association-rule based sequential classifiers for web-document prediction
Q Yang et al.
DATA MINING AND KNOWLEDGE DISCOVERY (2004)
Optimal algorithms for finding user access sessions from very large web logs
ZX Chen et al.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2003)
Unsupervised learning of mDTD extraction patterns for Web text mining
D Kim et al.
INFORMATION PROCESSING & MANAGEMENT (2003)
Relevance feedback and learning in content-based image search
HJ Zhang et al.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2003)
Web-log cleaning for constructing sequential classifiers
Q Yang et al.
APPLIED ARTIFICIAL INTELLIGENCE (2003)
Web page clustering using a self-organizing map of user navigation patterns
KA Smith et al.
DECISION SUPPORT SYSTEMS (2003)
Client-side monitoring for web mining
KD Fenstermacher et al.
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY (2003)
Design and evaluation of a multi-agent collaborative Web mining system
M Chau et al.
DECISION SUPPORT SYSTEMS (2003)
On using a warehouse to analyze web logs
KP Joshi et al.
DISTRIBUTED AND PARALLEL DATABASES (2003)
A novel Web usage mining approach for search engines
D Zhang et al.
COMPUTER NETWORKS (2002)
Personalization technology application to Internet content provider
YF Kuo et al.
EXPERT SYSTEMS WITH APPLICATIONS (2001)
Web personalization expert with combining collaborative filtering and association rule mining technique
CH Lee et al.
EXPERT SYSTEMS WITH APPLICATIONS (2001)
Mining patterns from graph traversals
A Nanopoulos et al.
DATA & KNOWLEDGE ENGINEERING (2001)
Web usage mining for Web site evaluation - Making a site better fit its users.
M Spiliopoulou
COMMUNICATIONS OF THE ACM (2000)
Automatic personalization based on Web usage mining - Web usage mining can help improve the scalability, accuracy, and flexibility of recommender systems.
B Mobasher et al.
COMMUNICATIONS OF THE ACM (2000)