Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results or best seller lists. In spite of their importance, methods of processing orders have received little attention. Only recently has research concerning object ordering become more common; in particular, some researchers have developed various… (More)
—The aim of transfer learning is to improve prediction accuracy on a target task by exploiting the training examples for tasks that are related to the target one. Transfer learning has received more attention in recent years, because this technique is considered to be helpful in reducing the cost of labeling. In this paper, we propose a very simple approach… (More)
Lists of ordered objects are widely used as representa-tional forms. Such ordered objects include Web search results or bestseller lists. Clustering is a useful data analysis technique for grouping mutually similar objects. To cluster orders, hierarchical clustering methods have been used together with dissimilarities defined between pairs of orders.… (More)
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of people who have tendencies similar to the user preference. Traditionally, the degree of preference is represented by a scale, for example, one that ranges from one to five. This… (More)
Iʼm Toshihiro Kamishima, and this is joint work with Shotaro Akaho and Jun Sakuma. Today, we would like to talk about fairness-aware data mining.
With the spread of data mining technologies and the accumulation of social data, such technologies and data are being used for determinations that seriously affect individuals' lives. For example, credit scoring is frequently determined based on the records of past credit data together with statistical prediction techniques. Needless to say, such… (More)
We advocate a new learning task that deals with orders of items, and we call this the Learning from Order Examples (LOE) task. The aim of the task is to acquire the rule that is used for estimating the proper order of a given unordered item set. The rule is acquired from training examples that are ordered item sets. We present several solution methods for… (More)
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results or bestseller lists. In spite of their importance, methods of processing orders have received little attention. However, research concerning orders has recently become common; in particular, researchers have developed various methods for the… (More)
Today I'd like to talk about a dimension reduction for supervised ordering .
Learning from cluster examples (LCE) is a hybrid task combining features of two common classification tasks: clustering and learning from examples. In LCE, each example is an object set with the true partition for the set, where the true partition is the one that users consider as the most appropriate for their aim among the possible partitions. The task is… (More)