A Survey on the Application of Process Mining to Smart Spaces Data

被引:3
作者
Bertrand, Yannis [1 ]
Van den Abbeele, Bram [1 ]
Veneruso, Silvestro [2 ]
Leotta, Francesco [2 ]
Mecella, Massimo [2 ]
Serral, Estefania [1 ]
机构
[1] Katholieke Univ Leuven, Res Ctr Informat Syst Engn LIRIS, Warmoesberg 26, B-1000 Brussels, Belgium
[2] Sapienza Univ Roma, Rome, Italy
来源
PROCESS MINING WORKSHOPS, ICPM 2022 | 2023年 / 468卷
关键词
Process mining; Smart spaces; Sensor logs; ACTIVITY RECOGNITION; BEHAVIOR; MODELS;
D O I
10.1007/978-3-031-27815-0_5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
During the last years, a number of studies have experimented with applying process mining (PM) techniques to smart spaces data. The general goal has been to automatically model human routines as if they were business processes. However, applying process-oriented techniques to smart spaces data comes with its own set of challenges. This paper surveys existing approaches that apply PM to smart spaces and analyses how they deal with the following challenges identified in the literature: choosing a modelling formalism for human behaviour; bridging the abstraction gap between sensor and event logs; and segmenting logs in traces. The added value of this article lies in providing the research community with a common ground for some important challenges that exist in this field and their respective solutions, and to assist further research efforts by outlining opportunities for future work.
引用
收藏
页码:57 / 70
页数:14
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