Searching Heterogeneous Personal Digital Traces
This addresses the challenge for users in organizing and retrieving their scattered digital information, though it is incremental as it builds on existing search and data modeling concepts.
The paper tackles the problem of searching heterogeneous personal digital traces by proposing a data model based on the six questions (what, when, where, who, why, how) to unify and index these traces, resulting in significantly improved search accuracy over traditional tools in experiments with real user data from sources like Facebook, Dropbox, and Gmail.
Digital traces of our lives are now constantly produced by various connected devices, internet services and interactions. Our actions result in a multitude of heterogeneous data objects, or traces, kept in various locations in the cloud or on local devices. Users have very few tools to organize, understand, and search the digital traces they produce. We propose a simple but flexible data model to aggregate, organize, and find personal information within a collection of a user's personal digital traces. Our model uses as basic dimensions the six questions: what, when, where, who, why, and how. These natural questions model universal aspects of a personal data collection and serve as unifying features of each personal data object, regardless of its source. We propose indexing and search techniques to aid users in searching for their past information in their unified personal digital data sets using our model. Experiments performed over real user data from a variety of data sources such as Facebook, Dropbox, and Gmail show that our approach significantly improves search accuracy when compared with traditional search tools.