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» Combining concept hierarchies and statistical topic models
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EMNLP
2009
14 years 9 months ago
Language Models Based on Semantic Composition
In this paper we propose a novel statistical language model to capture long-range semantic dependencies. Specifically, we apply the concept of semantic composition to the problem ...
Jeff Mitchell, Mirella Lapata
CIKM
2004
Springer
15 years 5 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann
MLDM
2005
Springer
15 years 5 months ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé
WWW
2008
ACM
16 years 9 days ago
Computable social patterns from sparse sensor data
We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
Dinh Q. Phung, Brett Adams, Svetha Venkatesh
ECCV
2006
Springer
16 years 1 months ago
Scene Classification Via pLSA
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Anna Bosch, Andrew Zisserman, Xavier Muñoz