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KDD
1998
ACM
101views Data Mining» more  KDD 1998»
15 years 3 months ago
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Ernest P. Chan, Santiago Garcia, Salim Roukos
RIAO
2007
15 years 1 months ago
Discriminative Fields for Modeling Semantic Concepts in Video
According to some current thinking, a very large number of semantic concepts could provide researcher a novel way to characterize video and be utilized for video retrieval and und...
Ming-yu Chen, Alexander G. Hauptmann
ICML
2001
IEEE
16 years 14 days ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ICPR
2000
IEEE
16 years 22 days ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
HIM
1997
Springer
162views Multimedia» more  HIM 1997»
15 years 3 months ago
Probabilistic Logical Information Retrieval for Content, Hypertext, and Database Querying
Classical retrieval models support content-oriented searching for documents using a set of words as data model. However, in hypertext and database applications we want to consider...
Thomas Rölleke, Markus Blömer