We discuss the problem of Web data extraction and describe an XML-based methodology whose goal extends far beyond simple "screen scraping." An ideal data extraction proc...
Fairness is an essential requirement of any operating system scheduler. Unfortunately, existing fair scheduling algorithms are either inaccurate or inefficient and non-scalable fo...
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
In this paper, we consider the problem of combining link and content analysis for community detection from networked data, such as paper citation networks and Word Wide Web. Most ...
Most of recommender systems try to find items that are most relevant to the older choices of a given user. Here we focus on the "surprise me" query: A user may be bored ...