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» Learning Rules from Distributed Data
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LREC
2008
125views Education» more  LREC 2008»
15 years 1 months ago
Adaptation of Relation Extraction Rules to New Domains
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
Feiyu Xu, Hans Uszkoreit, Hong Li, Niko Felger
71
Voted
IDEAL
2009
Springer
15 years 6 months ago
Clustering with XCS and Agglomerative Rule Merging
Abstract. In this paper, we present a more effective approach to clustering with eXtended Classifier System (XCS) which is divided into two phases. The first phase is the XCS le...
Liangdong Shi, Yinghuan Shi, Yang Gao
JIISIC
2001
15 years 1 months ago
Knowledge Component of a Multiagent Distributed Decision Support System
We have developed a distributed DSS capable to working in a dynamic way. That is, when a domain of an organization needs a new kind of information, the system looks for this infor...
Georgina Stegmayer, María Laura Caliusco, O...
96
Voted
DEBU
2000
95views more  DEBU 2000»
14 years 11 months ago
Accurately and Reliably Extracting Data from the Web: A Machine Learning Approach
A critical problem in developing information agents for the Web is accessing data that is formatted for human use. We have developed a set of tools for extracting data from web si...
Craig A. Knoblock, Kristina Lerman, Steven Minton,...
82
Voted
CLIMA
2004
15 years 1 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis