Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
We present and partially evaluate procedures for the extraction of noun+verb collocation candidates from German text corpora, along with their morphosyntactic preferences, especia...
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Database queries are often exploratory and users often find their queries return too many answers, many of them irrelevant. Existing work either categorizes or ranks the results t...
—User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., p...