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ABSTRACT Tag quality is an important factor to the success of social tagging systems and platforms. Users' domain expertise may influence they perceive tag quality. This study aims to explore how users of different domain experience (frequent user, occasional user, and non-user) perceive the quality of the same tags. We examined an online video community, Bilibili, which specializes in Anime, Comic and Games (ACG) subculture. We asked 60 users to watch 15 videos and rate the 95 tags of these videos, and found that: 1) Users with more domain expertise give higher ratings for tags' relevance to the videos and their retrieval value; 2) Occasional users have the lowest understandability rating, followed by non-users, and frequent users; 3) users think high-frequency tags are less suitable for retrieval. These results may provide insights to high quality tag selection for personalized recommendation and retrieval.
The Ambisonic technique has been widely used for soundfield recording and reproduction recently. However, the basicAmbisonic decoding method will break down when the play-back loudspeakers distribute unevenly. Various methods havebeen proposed to solve this problem. This paper introducesseveral improvements to a recently proposed Ambisonic de-coding method, the matching projection method, for unevenloudspeaker layouts. The first improvement is energy preserv-ing; the second is introducing the “in-phase” weight, and thethird is introducing partial projection coefficients. To eval-uate the improved method, we compared it with the origi-nal one and the all-round Ambisonic decoding method witha 2-dimension unevenly arranged loudspeaker array. The re-sult shows our method greatly improves the original methodwhere the loudspeaker arranges very sparsely or densely.