Gamification for IR: The query aspects game
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Gamification for IR : The query aspects game. / Di Nunzio, Giorgio Maria; Maistro, Maria; Zilio, Daniel.
I: CEUR Workshop Proceedings, Bind 1749, 01.01.2016.Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt
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TY - GEN
T1 - Gamification for IR
T2 - 3rd Italian Conference on Computational Linguistics, CLiC-it 2016 and 5th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, EVALITA 2016
AU - Di Nunzio, Giorgio Maria
AU - Maistro, Maria
AU - Zilio, Daniel
PY - 2016/1/1
Y1 - 2016/1/1
N2 - The creation of a labelled dataset for Information Retrieval (IR) purposes is a costly process. For this reason, a mix of crowdsourcing and active learning approaches have been proposed in the literature in order to assess the relevance of documents of a collection given a particular query at an affordable cost. In this paper, we present the design of the gamification of this interactive process that draws inspiration from recent works in the area of gamification for IR. In particular, we focus on three main points: i) we want to create a set of relevance judgements with the least effort by human assessors, ii) we use interactive search interfaces that use game mechanics, iii) we use Natural Language Processing (NLP) to collect different aspects of a query.
AB - The creation of a labelled dataset for Information Retrieval (IR) purposes is a costly process. For this reason, a mix of crowdsourcing and active learning approaches have been proposed in the literature in order to assess the relevance of documents of a collection given a particular query at an affordable cost. In this paper, we present the design of the gamification of this interactive process that draws inspiration from recent works in the area of gamification for IR. In particular, we focus on three main points: i) we want to create a set of relevance judgements with the least effort by human assessors, ii) we use interactive search interfaces that use game mechanics, iii) we use Natural Language Processing (NLP) to collect different aspects of a query.
UR - http://www.scopus.com/inward/record.url?scp=85009236662&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85009236662
VL - 1749
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
SN - 1613-0073
Y2 - 5 December 2016 through 7 December 2016
ER -
ID: 216517567