Understanding Latent Factors Using a GWAP
Recommender systems relying on latent factor models often appear as black boxes to their users. Semantic descriptions for the factors might help to mitigate this problem. Achieving this automatically is, however, a non-straightforward task due to the models' statistical nature. We present an output-agreement game that represents factors by means of sample items and motivates players to create such descriptions. A user study shows that the collected output actually reflects real-world characteristics of the factors.
Code (0)
등록된 구현이 없습니다.
Tasks
Recommendation SystemsSimilar Papers 제목 키워드 기반
Game Design Evaluation of GWAPs for Collecting Word Associations
GWAP design might have a tremendous effect on its popularity of course but also on the quality of the data collected. In this paper, a comparison is undertaken between two GWAPs for building term association lists, namel…
Game DesignLarge-Scale Acquisition of Commonsense Knowledge via a Quiz Game on a Dialogue System
Commonsense knowledge is essential for fully understanding language in many situations. We acquire large-scale commonsense knowledge from humans using a game with a purpose (GWAP) developed on a smartphone spoken dialogu…
Common Sense ReasoningQuestion AnsweringGlobal Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification
In this work, we first tackle the problem of simultaneous pixel-level localization and image-level classification with only image-level labels for fully convolutional network training. We investigate the global pooling m…
General Classificationimage-classificationImage Classificationobject-detection+2Aggregation Driven Progression System for GWAPs
As the uses of Games-With-A-Purpose (GWAPs) broadens, the systems that incorporate its usages have expanded in complexity. The types of annotations required within the NLP paradigm set such an example, where tasks can in…
Designing a GWAP for Collecting Naturally Produced Dialogues for Low Resourced Languages
In this paper we present a new method for collecting naturally generated dialogue data for a low resourced language, (specifically here{---}Uyghur). We plan to build a games with a purpose (GWAPs) to encourage native spe…