Type extension trees for feature construction and learning in relational domains

DOI10.1016/j.artint.2013.08.002zbMath1334.68186OpenAlexW2134768353WikidataQ62695798 ScholiaQ62695798MaRDI QIDQ490428

Andrea Passerini, Manfred Jaeger, Paolo Frasconi, Marco Lippi

Publication date: 27 August 2015

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2013.08.002

zbMATH Keywords

inductive logic programmingstatistical relational learningfeature discovery

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic programming (68N17)

Related Items (1)

Counts-of-counts similarity for prediction and search in relational data

Uses Software

• EMD
• EigenRank
• ArnetMiner

Cites Work

• An index to quantify an individual's scientific research output
• Relational information gain
• Finite model theory and its applications.
• Top-down induction of first-order logical decision trees
• The earth mover's distance as a metric for image retrieval
• Fast learning of relational kernels
• First order random forests: Learning relational classifiers with complex aggregates
• Probabilistic inductive logic programming. Theory and applications
• Markov logic networks
• Logical and Relational Learning
• Feature Discovery with Type Extension Trees
• The Monge-Kantorovich problem: achievements, connections, and perspectives
• Learning Theory and Kernel Machines
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