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CIKM
2008
Springer
15 years 6 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»
16 years 4 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»
16 years 4 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
15 years 8 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»
15 years 5 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