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Can I read An Overview of Distance and Similarity Functions for Structured Data on EtoBox?
An Overview of Distance and Similarity Functions for Structured Data by Santiago Ontañón is a Computer Science article available to read on EtoBox.
What is An Overview of Distance and Similarity Functions for Structured Data about?
The notions of distance and similarity play a key role in many machine learning approaches, and artificial intelligence in general, since they can serve as an organizing principle by which individuals classify objects, form concepts and make generalizations. While distance functions for propositional representations have been thoroughly studied, work on distance functions for structured representations, such as graphs, frames or logical clauses, has been carried out in different communities and is much less understood. Specifically, a significant amount of work that requires the use of a distance or similarity function for structured representations of data usually employs ad-hoc functions for specific applications. Therefore, the goal of this paper is to provide an overview of this work to identify connections between the work carried out in different areas and point out directions for future work.
Who reads An Overview of Distance and Similarity Functions for Structured Data?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Santiago Ontañón
- Publisher
- Springer Netherlands; Springer-Verlag; Kluwer Academic Publishers; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 0269-2821)
- Published
- 2020
- Language
- EN
- Field
- Computer Science (Physical Sciences)