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Continuous Time-Dependent kNN Join by Binary Sketches

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00100951" target="_blank" >RIV/00216224:14330/18:00100951 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1145/3216122.3216159" target="_blank" >http://dx.doi.org/10.1145/3216122.3216159</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3216122.3216159" target="_blank" >10.1145/3216122.3216159</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Continuous Time-Dependent kNN Join by Binary Sketches

  • Original language description

    An important functionality of current social applications is real-time recommendation, which is responsible for suggesting relevant published data to the users based on their preferences. By representing the users and the published data in a metric space, each user can be recommended with their k nearest neighbors among the published data. We consider the scenario when the relevance of a published data item to a user decreases as the data gets older, i.e., a time-dependent distance function is applied. We define the problem as the continuous time-dependent kNN join and provide a solution to a broad range of time-dependent functions. In addition, we propose a binary sketch-based approximation technique used to speed up the join evaluation by replacing expensive metric distance computations with cheap Hamming distances.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA16-18889S" target="_blank" >GA16-18889S: Big Data Analytics for Unstructured Data</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    IDEAS 2018 : 22nd International Database Engineering & Applications Symposium, June 18-20, 2018, Villa San Giovanni, Italy

  • ISBN

    9781450365277

  • ISSN

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    64-73

  • Publisher name

    ACM

  • Place of publication

    New York

  • Event location

    Villa San Giovanni, Italy

  • Event date

    Jun 18, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article