David Montoya
ABSTRACT
The typical Internet user has data spread over several devices and across several online systems. We demonstrate an open-source system for integrating user's data from different sources into a single Knowledge Base. Our system integrates data of different kinds into a coherent whole, starting with email messages, calendar, contacts, and location history. It is able to detect event periods in the user's location data and align them with calendar events. We will demonstrate how to query the system within and across different dimensions, and perform analytics over emails, events, and locations.
- S. Abiteboul, B. Andre, and D. Kaplan. "Managing your digital life". Communications of the ACM (2015). Google Scholar
Digital Library
- J. Broekstra, A. Kampman, and F. Van Harmelen. "Sesame: A generic architecture for storing and querying RDF and RDF schema". In: ISWC '02. Springer, 2002. Google ScholarDigital Library
- A. Cheyer, J. Park, and R. Giuli. IRIS: Integrate, Relate. Infer. Share. Tech. rep. DTIC Document, 2005.Google Scholar
- P. Christen. Data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection. Springer Science & Business Media, 2012. Google ScholarDigital Library
- M. Crispin. Internet Message Access protocol - version 4rev1. RFC 3501. IETF, Mar. 2003. Google ScholarDigital Library
- D. H. Crocker. Standard for the format of ARPA Internet text messages. RFC 822. IETF, Aug. 1982. Google ScholarDigital Library
- R. Cyganiak, D. Wood, and M. Lanthaler. RDF 1.1 Concepts and Abstract Syntax. W3C, Feb. 2014.Google Scholar
- C. Daboo. CardDAV: vCard Extensions to Web Distributed Authoring and Versioning (WebDAV). RFC 6352. IETF, Aug. 2011.Google Scholar
- C. Daboo, B. Desruisseaux, and L. Dusseault. Calendaring Extensions to WebDAV (CalDAV). RFC 4791. IETF, Mar. 2007.Google Scholar
- B. Desruisseaux. Internet Calendaring and Scheduling Core Object Specification (iCalendar). RFC 5545. IETF, Sept. 2009.Google Scholar
- S. Handschuh, K. Moller, and T. Groza. "The NEPOMUK project-on the way to the social semantic desktop". In: I-SEMANTICS '07. 2007.Google Scholar
- S. Harris, A. Seaborne, and E. Prud'hommeaux. SPARQL 1.1 Query Language. W3C, Mar. 2013.Google Scholar
- J. H. Kang, W. Welbourne, B. Stewart, and G. Borriello. "Extracting Places from Traces of Locations". In: WMASH '04. 2004. Google ScholarDigital Library
- T. Lovett, E. O'Neill, J. Irwin, and D. Pollington. "The calendar as a sensor: analysis and improvement using data fusion with social networks and location". In: UbiComp '10. 2010. Google ScholarDigital Library
- S. Perreault. vCard Format Specification. RFC 6350. IETF, Aug. 2011.Google Scholar
Index Terms
- Thymeflow, A Personal Knowledge Base with Spatio-temporal Data
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