850 research outputs found
Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata
Many social Web sites allow users to annotate the content with descriptive
metadata, such as tags, and more recently to organize content hierarchically.
These types of structured metadata provide valuable evidence for learning how a
community organizes knowledge. For instance, we can aggregate many personal
hierarchies into a common taxonomy, also known as a folksonomy, that will aid
users in visualizing and browsing social content, and also to help them in
organizing their own content. However, learning from social metadata presents
several challenges, since it is sparse, shallow, ambiguous, noisy, and
inconsistent. We describe an approach to folksonomy learning based on
relational clustering, which exploits structured metadata contained in personal
hierarchies. Our approach clusters similar hierarchies using their structure
and tag statistics, then incrementally weaves them into a deeper, bushier tree.
We study folksonomy learning using social metadata extracted from the
photo-sharing site Flickr, and demonstrate that the proposed approach addresses
the challenges. Moreover, comparing to previous work, the approach produces
larger, more accurate folksonomies, and in addition, scales better.Comment: 10 pages, To appear in the Proceedings of ACM SIGKDD Conference on
Knowledge Discovery and Data Mining(KDD) 201
J. L. Doob: Foundations of stochastic processes and probabilistic potential theory
During the three decades from 1930 to 1960 J. L. Doob was, with the possible
exception of Kolmogorov, the man most responsible for the transformation of the
study of probability to a mathematical discipline. His accomplishments were
recognized by both probabilists and other mathematicians in that he is the only
person ever elected to serve as president of both the IMS and the AMS. This
article is an attempt to discuss his contributions to two areas in which his
work was seminal, namely, the foundations of continuous parameter stochastic
processes and probabilistic potential theory.Comment: Published in at http://dx.doi.org/10.1214/09-AOP465 the Annals of
Probability (http://www.imstat.org/aop/) by the Institute of Mathematical
Statistics (http://www.imstat.org
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