Aspect-Based Similar Entity Search in Semantic Knowledge Graphs with Diversity-Awareness and Relaxation

Abstract

Structured knowledge bases are an increasingly important way for storing and retrieving information. Within such knowledge bases, an important search task is finding similar entities based on one or more example entities. We present QBEES, a novel framework for defining entity similarity based only on structural features, so-called aspects, of the entities, that naturally model potential interest profiles of a user submitting an ambiguous query. The aspect model provides natural diversity-awareness and includes query-dependent and query-independent entity ranking components. We present evaluation results with a number of existing entity list completion benchmarks, comparing to several state-of-the-art baselines.