Many individuals generate a flood of personal digital traces (e.g., emails, social media posts, web searches, calendars) as a byproduct of their daily activities. To facilitate querying and to support natural retrospective and prospective memory of these, a key problem is to integrate them in some sensible manner. For this purpose, based on research in the cognitive sciences, we propose a conceptual modeling language whose novel features include (i) the super-properties “who, what, when, where, why, how” applied uniformly to both documents and autobiographic events; and (ii) the ability to describe prototypical plans (“scripts”) for common everyday events, which in fact generate personal digital documents as traces. The scripts and wh-questions support the hierarchical organization and abstraction of the original data, thus helping end-users query it. We illustrate the use of our language through examples, provide formal semantics, and present an algorithm to recognize script instances.
CITATION STYLE
Kalokyri, V., Borgida, A., Marian, A., & Vianna, D. (2017). Semantic modeling and inference with episodic organization for managing personal digital traces: (Short paper). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10574 LNCS, pp. 273–280). Springer Verlag. https://doi.org/10.1007/978-3-319-69459-7_19
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