Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/143322| Título: | TSSEARCH |
| Autor: | Folgado, Duarte Barandas, Marília Antunes, Margarida Nunes, Maria Lua Liu, Hui Hartmann, Yale Schultz, Tanja Gamboa, Hugo |
| Palavras-chave: | Time series Subsequence search Distances Similarity measurements Query-based search Segmentation Python package |
| Data: | Jun-2022 |
| Resumo: | Subsequence search and distance measures are crucial tools in time series data mining. This paper presents our Python package entitled TSSEARCH, which provides a comprehensive set of methods for subsequence search and similarity measurement in time series. These methods are user-customizable for more flexibility and efficient integration into real deployment scenarios. TSSEARCH enables fast exploratory time series data analysis and was validated in the context of human activity recognition and indoor localization. |
| Descrição: | |
| Peer review: | yes |
| URI: | http://hdl.handle.net/10362/143322 |
| DOI: | https://doi.org/10.1016/j.softx.2022.101049 |
| ISSN: | 2352-7110 |
| Aparece nas colecções: | Home collection (FCT) |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| TSSEARCH_Time_Series_Subsequence_Search_Library.pdf | 537,5 kB | Adobe PDF | Ver/Abrir |
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