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Conference Papers Year : 2016

Quality Prediction in Collaborative Platforms: A Generic Approach by Heterogeneous Graphs

Abstract

As everyone can enrich or rather impoverish crowd-sourcing contents, it is a crucial need to continuously improve automatic quality contents assessment tools. Structural-based analysis methods developed for such quality prediction purposes generally handle a limited or manually fixed number of families of nodes and relations. This lack of genericity prevents existing algorithms for being adaptable to platforms evolutions. In this work, we propose a generic and adaptable algorithm, called HSQ, generalising various state-of-the-art models and allowing the consideration of graphs defined by an arbitrary number of nodes semantics. Evaluations performed over the two representative crowd-sourcing platforms Wikipedia and Stack Exchange state that the consideration of additional nodes semantics and relations improve the performances of state-of-the-art approaches.
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Dates and versions

hal-01690144 , version 1 (22-01-2018)

Identifiers

  • HAL Id : hal-01690144 , version 1
  • OATAO : 18795

Cite

Baptiste De La Robertie, Yoann Pitarch, Olivier Teste. Quality Prediction in Collaborative Platforms: A Generic Approach by Heterogeneous Graphs. 27th International Conference on Database and Expert Systems Applications (DEXA 2016), Sep 2016, Porto, Portugal. pp. 19-26. ⟨hal-01690144⟩
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