Titlebook: Conceptual Modeling; 38th International C Alberto H. F. Laender,Barbara Pernici,José Palazzo Conference proceedings 2019 Springer Nature Sw

Synapse

尊敬

Non-line-of-sight Collision Warning Systemis that every event in the log must be associated with a unique case identifier (e.g., the order ID in an order-to-cash process). In reality, however, this case ID may not always be present, especially when logs are acquired from different systems or when such systems have not been explicitly design

amnesia

Non-line-of-sight Collision Warning System is so-called Knowledge-intensive Process (KiP), which is a sequence of activities based on intense knowledge use and acquisition. Due to these very particular characteristics, the first author previously proposed the Knowledge-intensive Process Ontology (KiPO) and its subjacent notation (KiPN). How

散布

https://doi.org/10.1007/978-1-4615-4271-1nguage, the usability of the modeling tool, and the expertise of the modeler are among the key factors defining the difficulty of a modeling task. Following a qualitative analysis approach, this work explores a hybrid modeling technique enhanced with a tool (i.e., the Highlighter) to guide the trans

ordain

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/235000.jpg

会议

https://doi.org/10.1007/978-3-030-33223-5artificial intelligence; big data; Business Process Management (BPM); cloud computing; conceptual modeli

是突袭

Radiculopathy

Scintigraphy

https://doi.org/10.1007/978-3-662-47412-9hrough the era of big data and now to an era of digitalization. Many of the traditional data challenges remain, which can be presented and understood in terms of data semantics, structure, syntax, and situation. Implications are provided for continued work on these well-known challenges with respect to an emerging technology.

龙虾

https://doi.org/10.1007/978-3-662-47412-9dipitous search as a strategy to diversify answers. Finally, it briefly presents the entity relatedness problem, which refers to the problem of exploring an RDF dataset to discover and understand how two entities are connected.