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ICML
2004
IEEE
14 years 8 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICML
2000
IEEE
14 years 8 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
WWW
2008
ACM
14 years 8 months ago
Spatial variation in search engine queries
Local aspects of Web search -- associating Web content and queries with geography -- is a topic of growing interest. However, the underlying question of how spatial variation is m...
Lars Backstrom, Jon M. Kleinberg, Ravi Kumar, Jasm...
WWW
2008
ACM
14 years 8 months ago
Scalable querying services over fuzzy ontologies
Fuzzy ontologies are envisioned to be useful in the Semantic Web. Existing fuzzy ontology reasoners are not scalable enough to handle the scale of data that the Web provides. In t...
Jeff Z. Pan, Giorgos B. Stamou, Giorgos Stoilos, S...
WWW
2008
ACM
14 years 8 months ago
Mining the search trails of surfing crowds: identifying relevant websites from user activity
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
Mikhail Bilenko, Ryen W. White