The increasing availability of semantic data, which is commonly represented as entity-property-value triples, has enabled novel information retrieval applications. However, the magnitude of semantic data, in particular the large number of triples describing an entity, could overload users with excessive amounts of information. This has motivated fruitful research on automated generation of summaries for entity descriptions to satisfy users' information needs efficiently and effectively. We focus on this important topic of entity summarization, and present the first comprehensive survey of existing research. We review existing methods and evaluation efforts, and suggest directions for future work.
翻译:语义数据通常被作为实体-财产价值的三重数据,其可获得性日益增强,因此能够进行新的信息检索应用;然而,语义数据的规模,特别是描述一个实体的三重数据数量之大,可能给用户带来过多的信息,从而给用户带来过重的负担;这促使对实体描述的自动生成摘要进行富有成效的研究,以便高效率和高成效地满足用户的信息需求;我们集中关注实体总结这一重要议题,并介绍对现有研究的第一次全面调查;我们审查现有方法和评估工作,并提出未来工作的方向。