The purpose of this research is to investigate appropriate collaborative forecasting models, both for acceptable accuracy and effectiveness for information sharing via the Internet to partners. Several forecasting models were investigated in this research. For comparing the models, five years historical data are collected from a lathe machine manufacturer in Taiwan, and one of its partners – a ...

In online learning to rank we are faced with a tradeoff between exploring new, potentially superior rankers, and exploiting our preexisting knowledge of what rankers have performed well in the past. Multileaving methods offer an attractive approach to this problem since they can efficiently use online feedback to simultaneously evaluate a potentially arbitrary number of rankers. In this talk we...

This introduction gives a brief overview of the field of preference learning and, along the way, tries to establish a unified terminology. Special emphasis will be put on learning to rank, which is by now one of the most extensively studied problem tasks in preference learning and also prominently represented in this book. We propose a categorization of ranking problems into object ranking, ins...

Recently, social tag recommendation has gained more attention in web research, and many approaches were proposed, which can be classified into two types: rule-based and classification-based approaches. However, too much expert experience and manual work are needed in rule-based approaches, and its generalization is limited. Additionally, there are some essential barriers in classification-based...