NDLI: From documents to tasks: deriving user tasks from document usage patterns

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From documents to tasks: deriving user tasks from document usage patterns

Content Provider	ACM Digital Library
Author	Brdiczka, Oliver
Abstract	A typical knowledge worker is involved in multiple tasks and switches frequently between them every work day. These frequent switches become expensive because each task switch requires some recovery time as well as the reconstitution of task context. First task management support systems have been proposed in recent years in order to assist the user during these switches. However, these systems still need a fairly big amount of investment from the user side in order to either learn to use or train such a system. In order to reduce the necessary amount of training, this paper proposes a new approach for automatically estimating a user's tasks from document interactions in an unsupervised manner. While most previous approaches to task detection look at the content of documents or window titles, which might raise confidentiality and privacy issues, our approach only requires document identifiers and the temporal switch history between them as input. Our prototype system monitors a user's desktop activities and logs documents that have focus on the user's desktop by attributing a unique identifier to each of these documents. Retrieved documents are filtered by their dwell times and a document similarity matrix is estimated based on document frequencies and switches. A spectral clustering algorithm then groups documents into tasks using the derived similarity matrix. The described prototype system has been evaluated on user data of 29 days from 10 different subjects in a corporation. Obtained results indicate that the approach is better than previous approaches that use content.
Starting Page	285
Ending Page	288
Page Count	4
File Format	PDF
ISBN	9781605585154
DOI	10.1145/1719970.1720012
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-02-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	User task modeling Document clustering Automatic task identification
Content Type	Text
Resource Type	Article

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