RUS  ENG JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Model. Anal. Inform. Sist.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Model. Anal. Inform. Sist., 2016, Volume 23, Number 2, Pages 195–210 (Mi mais491)  

Dataflow-driven crowdsourcing: relational models and algorithms

D. A. Ustalov

N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences, Sofia Kovalevskaya str., 16, Yekaterinburg, 620990, Russia

Abstract: Recently, microtask crowdsourcing has become a popular approach for addressing various data mining problems. Crowdsourcing workflows for approaching such problems are composed of several data processing stages which require consistent representation for making the work reproducible. This paper is devoted to the problem of reproducibility and formalization of the microtask crowdsourcing process. A computational model for microtask crowdsourcing based on an extended relational model and a dataflow computational model has been proposed. The proposed collaborative dataflow computational model is designed for processing the input data sources by executing annotation stages and automatic synchronization stages simultaneously. Data processing stages and connections between them are expressed by using collaborative computation workflows represented as loosely connected directed acyclic graphs. A synchronous algorithm for executing such workflows has been described. The computational model has been evaluated by applying it to two tasks from the computational linguistics field: concept lexicalization refining in electronic thesauri and establishing hierarchical relations between such concepts. The “Add–Remove–Confirm” procedure is designed for adding the missing lexemes to the concepts while removing the odd ones. The “Genus–Species–Match” procedure is designed for establishing “is-a” relations between the concepts provided with the corresponding word pairs. The experiments involving both volunteers from popular online social networks and paid workers from crowdsourcing marketplaces confirm applicability of these procedures for enhancing lexical resources.

Keywords: crowdsourcing, dataflow model, relational model, computational linguistics.

Funding Agency Grant Number
Russian Foundation for Basic Research 16-37-00354_мол_а
Russian Humanitarian Science Foundation 13-04-12020
16-04-12019
The reported study was funded by RFBR according to the research project no. 16-37-00354 мол_а “Adaptive Crowdsourcing Methods for Linguistic Resources”. This work was supported by the Russian Foundation for the Humanities project no. 13-04-12020 “New Open Electronic Thesaurus for Russian” and project no. 16-04-12019 “RussNet and YARN thesauri integration”.


DOI: https://doi.org/10.18255/1818-1015-2016-2-195-210

Full text: PDF file (744 kB)
References: PDF file   HTML file

Bibliographic databases:

UDC: 004.048
Received: 02.04.2016

Citation: D. A. Ustalov, “Dataflow-driven crowdsourcing: relational models and algorithms”, Model. Anal. Inform. Sist., 23:2 (2016), 195–210

Citation in format AMSBIB
\Bibitem{Ust16}
\by D.~A.~Ustalov
\paper Dataflow-driven crowdsourcing: relational models and algorithms
\jour Model. Anal. Inform. Sist.
\yr 2016
\vol 23
\issue 2
\pages 195--210
\mathnet{http://mi.mathnet.ru/mais491}
\crossref{https://doi.org/10.18255/1818-1015-2016-2-195-210}
\mathscinet{http://www.ams.org/mathscinet-getitem?mr=3504589}
\elib{http://elibrary.ru/item.asp?id=25810352}


Linking options:
  • http://mi.mathnet.ru/eng/mais491
  • http://mi.mathnet.ru/eng/mais/v23/i2/p195

    SHARE: VKontakte.ru FaceBook Twitter Mail.ru Livejournal Memori.ru


    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles
  • Моделирование и анализ информационных систем
    Number of views:
    This page:130
    Full text:56
    References:22

     
    Contact us:
     Terms of Use  Registration  Logotypes © Steklov Mathematical Institute RAS, 2020