NOVÁK, David, Petr VOLNÝ and Pavel ZEZULA. Generic Subsequence Matching Framework: Modularity, Flexibility, Efficiency. Cornell University Library, 2012. eprint arXiv:1206.2510.
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Basic information
Original name Generic Subsequence Matching Framework: Modularity, Flexibility, Efficiency
Authors NOVÁK, David (203 Czech Republic, guarantor, belonging to the institution), Petr VOLNÝ (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition eprint arXiv:1206.2510, 2012.
Publisher Cornell University Library
Other information
Original language English
Type of outcome Special-purpose publication
Field of Study Informatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14330/12:00057555
Organization Fakulta informatiky - Repository
Keywords in English subsequence matching; metric indexing; framework
Links GAP103/10/0886, research and development project.GPP202/10/P220, research and development project.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 1/9/2020 12:46.
Abstract
Subsequence matching has appeared to be an ideal approach for solving many problems related to the fields of data mining and similarity retrieval. It has been shown that almost any data class (audio, image, biometrics, signals) is or can be represented by some kind of time series or string of symbols, which can be seen as an input for various subsequence matching approaches. The variety of data types, specific tasks and their partial or full solutions is so wide that the choice, implementation and parametrization of a suitable solution for a given task might be complicated and time-consuming; a possibly fruitful combination of fragments from different research areas may not be obvious nor easy to realize. The leading authors of this field also mention the implementation bias that makes difficult a proper comparison of competing approaches. Therefore we present a new generic Subsequence Matching Framework (SMF) that tries to overcome the aforementioned problems by a uniform frame that simplifies and speeds up the design, development and evaluation of subsequence matching related systems. We identify several relatively separate subtasks solved differently over the literature and SMF enables to combine them in straightforward manner achieving new quality and efficiency. This framework can be used in many application domains and its components can be reused effectively. Its strictly modular architecture and openness enables also involvement of efficient solutions from different fields, for instance efficient metric-based indexes. This is an extended version of a paper published on DEXA 2012.
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