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Searching the longest common subsequences in distorted data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86094721" target="_blank" >RIV/61989100:27240/15:86094721 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27350/15:86094721 RIV/61989100:27740/15:86094721

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Searching the longest common subsequences in distorted data

  • Original language description

    Many models and artificial intelligence methods work with the inputs in the form of time series. Success of many of them strongly depends on ability to quickly and precisely compare two time series or search the mutual parts. Such ability is especially crucial while recognizing characteristic patterns, indexing, prediction or compression. There are many algorithms able to handle that, however, many of them fail while processing distorted data. Unfortunately, the distortion is natural for many types of data collections, e.g. for measurements of natural phenomena such as precipitations, river discharge volume etc. This paper discusses the possibilities of searching such common subsequences in time series and presents a new approach for searching the longest common subsequences in distorted data. This approach is based on modified the dynamic time warping algorithm, which allows the effective processing distorted time series data.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    27th European Modeling and Simulation Symposium, EMSS 2015

  • ISBN

    978-88-97999-48-5

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    84-92

  • Publisher name

    Dime University of Genoa

  • Place of publication

    Genova

  • Event location

    Bergeggi

  • Event date

    Sep 21, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article