Sciweavers

Share
ICML
2007
IEEE

Learning for efficient retrieval of structured data with noisy queries

10 years 2 days ago
Learning for efficient retrieval of structured data with noisy queries
Increasingly large collections of structured data necessitate the development of efficient, noise-tolerant retrieval tools. In this work, we consider this issue and describe an approach to learn a similarity function that is not only accurate, but that also increases the effectiveness of retrieval data structures. We present an algorithm that uses functional gradient boosting to maximize both retrieval accuracy and the retrieval efficiency of vantage point trees. We demonstrate the effectiveness of our approach on two datasets, including a moderately sized real-world dataset of folk music.
Charles Parker, Alan Fern, Prasad Tadepalli
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2007
Where ICML
Authors Charles Parker, Alan Fern, Prasad Tadepalli
Comments (0)
books