Measuring the Eccentricity of Items
This work addresses the need for better differentiation of items in the long tail for recommendation systems, though it appears incremental as it builds on existing concepts of popularity and user behavior.
The paper tackled the problem of distinguishing between different types of tail items in recommendation systems by proposing a novel metric called item eccentricity, which measures how items are consumed by eccentric users, and found that eccentricity is stable over time and effectively separates items in the tail.
The long-tail phenomenon tells us that there are many items in the tail. However, not all tail items are the same. Each item acquires different kinds of users. Some items are loved by the general public, while some items are consumed by eccentric fans. In this paper, we propose a novel metric, item eccentricity, to incorporate this difference between consumers of the items. Eccentric items are defined as items that are consumed by eccentric users. We used this metric to analyze two real-world datasets of music and movies and observed the characteristics of items in terms of eccentricity. The results showed that our defined eccentricity of an item does not change much over time, and classified eccentric and noneccentric items present significantly distinct characteristics. The proposed metric effectively separates the eccentric and noneccentric items mixed in the tail, which could not be done with the previous measures, which only consider the popularity of items.