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ACL
2004
13 years 7 months ago
Learning to Resolve Bridging References
We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references. We fin...
Massimo Poesio, Rahul Mehta, Axel Maroudas, Janet ...
PRL
2007
180views more  PRL 2007»
13 years 5 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...
SIGIR
2006
ACM
13 years 11 months ago
Type less, find more: fast autocompletion search with a succinct index
We consider the following full-text search autocompletion feature. Imagine a user of a search engine typing a query. Then with every letter being typed, we would like an instant d...
Holger Bast, Ingmar Weber
CVPR
2003
IEEE
14 years 7 months ago
Learning Affinity Functions for Image Segmentation: Combining Patch-based and Gradient-based Approaches
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...
Charless Fowlkes, David R. Martin, Jitendra Malik
BMCBI
2005
152views more  BMCBI 2005»
13 years 5 months ago
Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER
Background: Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling ar...
Markus Wistrand, Erik L. L. Sonnhammer