Participatory Art Museum: Collecting and Modeling Crowd Opinions

Authors

  • Xiaoyu Zeng The University of Texas at Austin
  • Ruohan Zhang The University of Texas at Austin

DOI:

https://doi.org/10.1609/aaai.v31i1.11072

Keywords:

Participatory Museum, Crowdsourcing, Semantic Embedding

Abstract

We collect public opinions on museum artworks using online crowdsourcing techniques. We ask two research questions. First, do crowd opinions on artworks differ from expert interpretations? Second, how can museum manage large amount of crowd opinions, such that users can efficiently retrieve useful information? We address these questions through opinion modeling via semantic embedding and dimension reduction.

AAAI-2017 Proceedings Cover

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Published

2017-02-12

How to Cite

Zeng, X., & Zhang, R. (2017). Participatory Art Museum: Collecting and Modeling Crowd Opinions. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11072

Issue

Vol. 31 No. 1 (2017): Thirty-First AAAI Conference on Artificial Intelligence

Section

Student Abstract Track