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CIKM
2008
Springer
13 years 10 months ago
Combining concept hierarchies and statistical topic models
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
14 years 8 months ago
Scaling up text classification for large file systems
: We combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifie...
George Forman, Shyamsundar Rajaram
EDBT
2008
ACM
178views Database» more  EDBT 2008»
14 years 8 months ago
An inductive database and query language in the relational model
In the demonstration, we will present the concepts and an implementation of an inductive database ? as proposed by Imielinski and Mannila ? in the relational model. The goal is to...
Lothar Richter, Jörg Wicker, Kristina Kessler...
COOPIS
2004
IEEE
13 years 11 months ago
Comparing Approaches for Semantic Service Description and Matchmaking
Matching descriptions of user requirements against descriptions of service capabilities is crucial for the discovery of appropriate services for a given task. To improve the precis...
Sven Schade, Arnd Sahlmann, Michael Lutz, Florian ...
DGO
2007
192views Education» more  DGO 2007»
13 years 9 months ago
D-HOTM: distributed higher order text mining
We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...
William M. Pottenger