QBEES: query-by-example entity search in semantic knowledge graphs based on maximal aspects, 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 on structural features, so-called aspects and maximal aspects of the entities, that naturally model potential interest profiles of a user submitting an ambiguous query. Our approach based on maximal aspects 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.

Semantically Enriched Models for Entity Ranking

“…In their approach called QBEES, Metzger et al [39] aim to explicitly capture the different potential user interests behind the provided examples. Each entity e is characterized based on three kinds of aspects:…”

“…One of the main challenges in similar entity search, i.e., in computing score E (e;E q ), is the inherent ambiguity because of the lack of an explicit user query. Such situations are typically addressed using diversity-aware Algorithm 4.1: QBEES [39] Input: set of example entities, E q Output: top-k similar entities, E R…”

“…We omit the proof here and refer to [39] for details. According to the above theorem, the partitioning provided by the maximal aspects of E q can guide the process of selecting a diverse set of result entities E R that have the highest similarity to E q .…”

“…For that, all aspects that are subsets of A(E q ) need to be considered and checked for the two criteria defining a maximal aspect. For further details on how to efficiently perform this, we refer to [39]. • Constraining maximal aspects on typical types.…”

“…• Ranking maximal aspects. "The resulting maximal aspects are of different specificity and thus quality" [39]. Therefore, a ranking needs to be established, and maximal aspects will be considered in that order.…”