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» Label Ranking Methods based on the Plackett-Luce Model
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CIVR
2008
Springer
166views Image Analysis» more  CIVR 2008»
15 years 1 months ago
A probabilistic ranking framework using unobservable binary events for video search
Recent content-based video retrieval systems combine output of concept detectors (also known as high-level features) with text obtained through automatic speech recognition. This ...
Robin Aly, Djoerd Hiemstra, Arjen P. de Vries, Fra...
WWW
2011
ACM
14 years 6 months ago
Identifying primary content from web pages and its application to web search ranking
Web pages are usually highly structured documents. In some documents, content with different functionality is laid out in blocks, some merely supporting the main discourse. In ot...
Srinivas Vadrevu, Emre Velipasaoglu
MCS
2004
Springer
15 years 5 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel
ICDAR
2011
IEEE
13 years 11 months ago
Co-training for Handwritten Word Recognition
—To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on...
Volkmar Frinken, Andreas Fischer, Horst Bunke, Ali...
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 5 months ago
Use of a genetic algorithm in brill's transformation-based part-of-speech tagger
The tagging problem in natural language processing is to find a way to label every word in a text as a particular part of speech, e.g., proper noun. An effective way of solving th...
Garnett Carl Wilson, Malcolm I. Heywood