Abstract
ABSTRACTThis paper discusses a gamification design for knowledge base refinement. We present a simulation model for game playing and examine the possibility of estimating the effects of game rule design. The maintenance of a knowledge base involves human intervention and is one of the application domains of human computation. Using the concept of crowdsourcing, refinement tasks can be delegated to many casual users over a network. In addition, gamification, such as games with a purpose (GWAP), is a useful idea to motivate workers in crowdsourcing by making tasks enjoyable. For effective gamification, designing the game rules is critical. In this paper, we present a model for simulating the gamified knowledge base refinement process to estimate the effects of different game rule designs beforehand. We use a rental apartment FAQ system as an example knowledge base and show that by invoking game playing when a problem is found in a knowledge base, it can be properly updated. In addition, we discuss the effectiveness of using a calibration quiz to estimate the reliability of users.
Highlights
The web has evolved into a platform on which knowledge content is created and shared
In the first case of simulation experiments, we examined whether knowledge contents can be refined even when a quiz contains multiple keywords
We examined the effect of a calibration quiz
Summary
The web has evolved into a platform on which knowledge content is created and shared. Such technologies as data mining or machine learning have made significant advancements for extracting meaningful data from large data. Constructing a highquality knowledge base still requires human participation, especially from domain experts. How to utilize the power of many casual users is crucial. Crowdsourcing is one notable framework to tackle this problem (Doan, Ramakrishnan, & Halevy 2011; Howe 2009)
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