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Abstract: . Objects with higher structural complexity often cannot be described by feature vectors without losing important structural information. Several types of structured objects can be represented adequately by labeled graphs. The similarity of such descriptions is difficult to define and to compute. However, many algorithms in machine learning, knowledge discovery, pattern recognition and classification are based on the estimation of the similarity between the analysed objects. In order to... (Update)
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BibTeX entry: (Update)
Kristina Schadler and Fritz Wysotzki. A connectionist approach to distance-based analysis of relational data. In Xiaohui Liu, Paul Cohen, and Michael Berthold, editors, Advances in Intelligent Data Analysis. Reasoning about Data. Proc. of the IDA-97, pages 137--148, Berlin Heidelberg New York, 1997. Springer. http://citeseer.ist.psu.edu/article/schadler97connectionist.html More
@inproceedings{ schadler97connectionist,
author = "Kristina Schadler and Fritz Wysotzki",
title = "A Connectionist Approach to Structural Simiarity Determination as a Basis of Clustering, Classification and Feature Detection",
booktitle = "Principles of Data Mining and Knowledge Discovery",
pages = "254-264",
year = "1997",
url = "citeseer.ist.psu.edu/article/schadler97connectionist.html" }
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