Assessment of semantic similarity in entities under monitoring: A systematic literature mapping

Abstract

The detection and evaluation of semantically similar entities in measurement projects is a key asset for real-time decision making because it allows reusing their knowledge and previous experiences. In this way, the objective of this work is to map the thematic area of data stream processing to identify the topics that have been investigated in the detection of semantically similar entities. From the methodological point of view, a systematic mapping study was conducted obtaining 2,122 articles. Thus, 111 were kept refining the search strategy, and 25 were considered once the filters were applied jointly with the inclusion/exclusion criteria. After reading the 25 documents, just 6 were pertinent and allowed answering the research questions aligned with the research objective. The semantic similarity applied to entities under monitoring in the measurement and evaluation projects is a challenge. Real-time decision making depends on the obtained measures, the monitored entity, and the context in which it is immersed.