We present iTag, a personalized tag recommendation system for blogs. iTag improves on the state-of-the-art in tag recommendation systems in two ways. First, iTag has much higher p...
This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is...
Mobile phones are becoming a primary platform for information access and when coupled with recommender systems technologies they can become key tools for mobile users both for lei...
Recommender systems, notably collaborative and hybrid information filtering approaches, vitally depend on neighborhood formation, i.e., selecting small subsets of most relevant pee...
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...