An activity based data model for desktop querying

With the introduction of a variety of desktop search systems by popular search engines as well as the Mac OS operating system, it is now possible to conduct keyword search across many types of documents. However, this type of search only helps the users locate a very specific piece of information that they are looking for. Furthermore, it is possible to locate this information only if the document contains some keywords and the user remembers the appropriate keywords. There are many cases where this may not be true especially for searches involving multimedia documents. However, a personal computer contains a rich set of associations that link files together. We argue that these associations can be used easily to answer more complex queries. For example, most files will have temporal and spatial information. Hence, files created at the same time or place may have relationships to each other. Similarly, files in the same directory or people addressed in the same email may be related to each other in some way. Furthermore, we can define a structure called “activities” that makes use of these associations to help user accomplish more complicated information needs. Intuitively, we argue that a person uses a personal computer to store information relevant to various activities she or he is involved in. Files may be related to activities either directly or indirectly with some degree of relationship. In this paper, we define a simple model of an activity and show the types of queries that can be answered using the activity model. Our model assumes that activities can involve files that are related to each other in many different ways: a period of time that may contain disjoint intervals, different locations, a group of people that we interact with and various combination of these types of associations. Furthermore, files may be related to multiple activities independent of their participation in one activity. Finally, our model aims to find the best indicators of an activity for a specific user and computer based on the data provided by that user.