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Dissimilarity measure for collections of objects  (Make Corrections)  
and values Petko Valtchev and J'erome Euzenat INRIA Rhone-Alpes ZIRST, 655...



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Abstract: Automatic classification may be used in object knowledge bases in order to suggest hypothesis about the structure of the available object sets. Yet its direct application meets some difficulties due to the way data is represented: attributes relating objects, multi-valued attributes, non-standard and external data types used in object descriptions. (Update)

Active bibliography (related documents):   More   All
0.9:   Automatic Taxonomy Building Within an Object Formalism - Valtchev (1997)   (Correct)
0.5:   Why and How to Define a Similarity Measure for Object Based.. - Gilles Bisson (1995)   (Correct)
0.5:   Data Representation for EMG Case Collection and Management - Bielikova, Navrat, Smolarova   (Correct)

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0.4:   Towards Formal Knowledge Intelligibility At the Semiotic Level - Euzenat (2000)   (Correct)
0.3:   Classification of Concepts Through Products of Concepts and.. - Petko Valtchev (1995)   (Correct)
0.2:   An Integrative Proximity Measure for Ontology Alignment - Euzenat, Valtchev (2003)   (Correct)

BibTeX entry:   (Update)

@misc{ petko-dissimilarity,
  author = "And Values Petko",
  title = "Dissimilarity Measure for Collections of Objects",
  url = "citeseer.ist.psu.edu/694053.html" }
Citations (may not include all citations):
349   Knowledge acquisition via incremental conceptual clustering (context) - Fisher - 1987
153   Autoclass: A bayesian classification system (context) - Cheeseman, Kelly et al. - 1988
151   Algorithms and Applications (context) - Ahuja, Magnanti et al. - 1993
145   Machine learning: an Artificial Intelligence approach (context) - Michalski, Stepp - 1983
88   Learning trees and rules with set-valued features - Cohen - 1996
60   Development and application of a metric on semantic nets (context) - Rada, Mili et al. - 1989
35   Conceptual clustering in a first order logic representation - Bisson - 1992
30   Knowledge discovery in databases (context) - Piatetsky-Shapiro, Frawley - 1991
19   Why and how to define a similarity measure for object-based .. - Bisson - 1995
9   Incremental structuring of knowledge bases - Godin, Mineau et al. - 1995
6   INRIA Rhone-Alpes (context) - project, reference - 1995
6   Hierarchical clustering of composite objects with variable n.. - Ketterlin, Gancarski et al. - 1995
5   Classification of concepts through products of concepts and .. - Valtchev, Euzenat - 1996
3   Conceptual clustering in structured domains: a theory guided.. (context) - Esposito - 1994
2   Neuromyosys a diagnosis knowledge based system for emg (context) - Zi'ebelin, Vila et al. - 1994
2   Brief overview of t-tree: the Tropes taxonomy building tool - Euzenat - 1993
2   chapter Concept formation in structured domains (context) - Thompson, Langley et al. - 1991
1   Identification et exploitation des types dans un mod`ele de .. (context) - Capponi - 1995
1   Lecture notes in statistics (context) - van Cutsem, dissimilarity - 1994
1   Objects, types and constraints as classification schemes (context) - Capponi, Euzenat et al. - 1995

Documents on the same site (http://www.iro.umontreal.ca/%7Evaltchev/valtchev_papers.html):   More
Similarity-based Clustering versus Galois lattice building: .. - Valtchev, Missaoui   (Correct)
Extracting Formal Concepts out of Relational Data - Valtchev, Hacene, Huchard.. (2003)   (Correct)
Building Classes in Object-Based Languages by Automatic Clustering - Valtchev (1999)   (Correct)

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