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» Using Decision Trees to Construct a Practical Parser
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NIPS
2004
13 years 9 months ago
Using Random Forests in the Structured Language Model
In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
Peng Xu, Frederick Jelinek
ICDE
2010
IEEE
192views Database» more  ICDE 2010»
14 years 2 months ago
XML reasoning made practical
— We present a tool for the static analysis of XPath queries and XML Schemas. The tool introduces techniques used in the field of verification (such as binary decision diagrams...
Pierre Genevès, Nabil Layaïda
TJS
2010
182views more  TJS 2010»
13 years 5 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
MLMI
2004
Springer
14 years 26 days ago
Shallow Dialogue Processing Using Machine Learning Algorithms (or Not)
This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and ...
Andrei Popescu-Belis, Alexander Clark, Maria Georg...
VLDB
1998
ACM
120views Database» more  VLDB 1998»
13 years 11 months ago
PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning
Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each c...
Rajeev Rastogi, Kyuseok Shim