Abstract
This chapter presents various fundamental building blocks of a similarity search system from the ground up. We start by introducing the attribute-based object representation that is widely used for representing real-world entities on the web as well as in similarity search systems. We then describe the various attribute types as well as measures used to quantify similarity and dissimilarity for specific attribute types. We also touch upon the interchangeability between the notions of similarity and dissimilarity, and illustrate the various transformations that could be applied to transform a similarity measure to a measure of dissimilarity.
| Original language | English |
|---|---|
| Title of host publication | SpringerBriefs in Computer Science |
| Publisher | Springer |
| Pages | 13-18 |
| Number of pages | 6 |
| Edition | 9783319212562 |
| DOIs | |
| Publication status | Published - 01 Jan 2015 |
| Externally published | Yes |
Publication series
| Name | SpringerBriefs in Computer Science |
|---|---|
| Number | 9783319212562 |
| ISSN (Print) | 2191-5768 |
| ISSN (Electronic) | 2191-5776 |
Keywords
- Attribute type
- Categorical attribute
- Dynamic time warping
- Levenshtein distance
- Numeric attribute
ASJC Scopus subject areas
- Computer Science(all)
Cite this
Deepak, P., & Deshpande, P. M. (2015). Fundamentals of similarity search. In SpringerBriefs in Computer Science (9783319212562 ed., pp. 13-18). (SpringerBriefs in Computer Science; No. 9783319212562). Springer. https://doi.org/10.1007/978-3-319-21257-9_2