A Systematic Literature Mapping on the Similar Semantically Entities in Measurement Projects

Context: Detecting and evaluating semantically similar entities in measurement projects is a key asset for real-time decision making because allows reusing their knowledge and previous experiences. Objective: The goal 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. Method: A systematic mapping study was conducted obtaining 1998 articles. Thus, 106 were kept refining the search strategy, and 38 were considered once the filters were applied jointly with the inclusion/exclusion criteria. Conclusion: After reading the 38 documents, just 4 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. The real-time decision making depends on the obtained measures, the monitored entity and the context in which it is immersed.