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Erschienen in:
Document Analysis and Retrieval Tasks in Scientific Digital Libraries Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Recommendation of Ideas and Antagonists for Crowdsourcing Platform Witology

verfasst von : Dmitry I. Ignatov, Maria Mikhailova, Alexandra Yu. Zakirova, Alexander Malioukov

Erschienen in: Information Retrieval

Verlag: Springer International Publishing

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Abstract

This paper introduces several recommender methods for crowdsourcing platforms. These methods are based on modern data analysis approaches for object-attribute data, such as Formal Concept Analysis and biclustering. The use of the proposed techniques is illustrated by the results of recommendation of ideas and antagonists for crowdsourcing platform Witology. In particular we show how the quality of antagonists recommender can be improved by usage of biclusters as focal areas for distance and similarity calculation.

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Vorheriges Kapitel A Comparative Evaluation of Statistical Part-of-Speech Taggers for Russian
Nächstes Kapitel Modelling Movement of Stock Market Indexes with Data from Emoticons of Twitter Users
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Metadaten
Titel
Recommendation of Ideas and Antagonists for Crowdsourcing Platform Witology
verfasst von
Dmitry I. Ignatov
Maria Mikhailova
Alexandra Yu. Zakirova
Alexander Malioukov
Copyright-Jahr
2015
Buch
Information Retrieval

Print ISBN: 978-3-319-25484-5

Electronic ISBN: 978-3-319-25485-2

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-25485-2_9

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