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Weber Nicolas, Lindstaedt Stefanie

A User Centered Approach for Quality Assessment in Social Systems

KMIS, 2011

Analyzing the meaning of quality in information systems has a long tradition. As a result of the increasing amount of user generated content on the web, addressing quality is more relevant than ever. Since information is produced and consumed by different people in various contexts the perception of quality is always closely tied to the users’ situation. This work proposes an approach for assessing quality in social systems with respect to the users’ current needs.

Granitzer Michael, Rath Andreas S., Kröll Mark, Ipsmiller D., Devaurs Didier, Weber Nicolas, Lindstaedt Stefanie , Seifert C.

Machine Learning based Work Task Classification

Journal of Digital Information Management, 2009

Increasing the productivity of a knowledgeworker via intelligent applications requires the identification ofa user’s current work task, i.e. the current work context a userresides in. In this work we present and evaluate machine learningbased work task detection methods. By viewing a work taskas sequence of digital interaction patterns of mouse clicks andkey strokes, we present (i) a methodology for recording thoseuser interactions and (ii) an in-depth analysis of supervised classificationmodels for classifying work tasks in two different scenarios:a task centric scenario and a user centric scenario. Weanalyze different supervised classification models, feature typesand feature selection methods on a laboratory as well as a realworld data set. Results show satisfiable accuracy and high useracceptance by using relatively simple types of features.

Kröll Mark, Rath Andreas S., Weber Nicolas, Lindstaedt Stefanie , Granitzer Michael

Task Instance Classification via Graph Kernels

Mining and Learning with Graphs (MLG 07), Florenz, Italy, August 1-3, 2007, 2007

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