Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering
Proceedings of the the seventh ACM conference on Hypertext
A localized algorithm for parallel association mining
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Document Categorization and Query Generation on the World Wide WebUsing WebACE
Artificial Intelligence Review - Special issue on data mining on the Internet
Automatic personalization based on Web usage mining
Communications of the ACM
Document ranking based upon Markov chains
Information Processing and Management: an International Journal
An efficient approach to discovering knowledge from large databases
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Personalized hypermedia and international privacy
Communications of the ACM - The Adaptive Web
Personalization of Supermarket Product Recommendations
Data Mining and Knowledge Discovery
Hyperlink Analysis for the Web
IEEE Internet Computing
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Helping Online Customers Decide through Web Personalization
IEEE Intelligent Systems
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
ICWL '02 Proceedings of the First International Conference on Advances in Web-Based Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A General Incremental Technique for Maintaining Discovered Association Rules
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Mining Indirect Associations in Web Data
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
SIAM Journal on Discrete Mathematics
Evaluation of web usage mining approaches for user's next request prediction
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
The Influence of Indirect Association Rules on Recommendation Ranking Lists
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
An efficient approach to mining indirect associations
Journal of Intelligent Information Systems
AdROSA-Adaptive personalization of web advertising
Information Sciences: an International Journal
ROSA: multi-agent system for web services personalization
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
Efficient mining of indirect associations using HI-mine
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Mining temporal indirect associations
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Adjustment of indirect association rules for the web
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
Simulating the effectiveness of using association rules for recommendation systems
AsiaSim'04 Proceedings of the Third Asian simulation conference on Systems Modeling and Simulation: theory and applications
Mining indirect association rules
ICDM'04 Proceedings of the 4th international conference on Advances in Data Mining: applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications
Recsplorer: recommendation algorithms based on precedence mining
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Beyond the usual suspects: context-aware revisitation support
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
A layered approach to revisitation prediction
ICWE'11 Proceedings of the 11th international conference on Web engineering
Knowledge discovery in data using formal concept analysis and random projections
International Journal of Applied Mathematics and Computer Science
Client- and server-side revisitation prediction with SUPRA
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Indirect weighted association rules mining for academic network collaboration recommendations
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
A Multimedia Recommender System
ACM Transactions on Internet Technology (TOIT)
| Hi-index | 0.00 |
Classical association rules, here called "direct", reflect relationships existing between items that relatively often co-occur in common transactions. In the web domain, items correspond to pages and transactions to user sessions. The main idea of the new approach presented is to discover indirect associations existing between pages that rarely occur together but there are other, "third" pages, called transitive, with which they appear relatively frequently. Two types of indirect associations rules are described in the paper: partial indirect associations and complete ones. The former respect single transitive pages, while the latter cover all existing transitive pages. The presented IDARM* Algorithm extracts complete indirect association rules with their important measure-confidence-using pre-calculated direct rules. Both direct and indirect rules are joined into one set of complex association rules, which may be used for the recommendation of web pages. Performed experiments revealed the usefulness of indirect rules for the extension of a typical recommendation list. They also deliver new knowledge not available to direct ones. The relation between ranking lists created on the basis of direct association rules as well as hyperlinks existing on web pages is also examined.