| abstract |
A recommendation system and method uses data structured according to an indicator-based recommendation paradigm. Items to be considered for recommendation are stored in a text retrieval system, along with associated meta-data such as title and description. To these conventional characteristics are added additional characteristics known as indicators which are derived from an analysis of the usage of the system by users. This indicator-based system provides a more robust recommendation system that is able to capture a greater depth and variety of real-world relationships among items, and is able to handle p-adic systems and systems with ternary or higher relations. |