Augmenting transportation-related recommendations through data mining
Source: International Journal of Advanced Intelligence Paradigms, Volume 2, Number 1, 30 November 2009 , pp. 78-89(12)
Publisher: Inderscience Publishers
Abstract:This paper reports on the exploitation of data mining techniques during the formulation of purposeful association rules out of the transactions' database of a transportation management system. The rules' construction is performed through an elaborated version of the AprioriTid algorithm. The proposed algorithm is generic and capable to construct such rules by creating a large set of related items. The constructed rules can be used by the system's recommender module, which is responsible for providing recommendations to the associated users. The recommendation process takes into account the constructed rules and techniques that derive from the area of Collaborative Filtering (CF).
Document Type: Research article
Publication date: 2009-11-30
- The International Journal of Advanced Intelligence Paradigms fosters the exchange and dissemination of applications and case studies in the area of advanced intelligence paradigms among professionals in education and research. The thrust of the journal is to publish papers dealing with the design, development, testing, implementation and management of advanced intelligent systems and also to provide practical guidelines in the development and management of these systems. The International Journal of Advanced Intelligence Paradigms will publish both archival articles and broader assessments of current trends. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.