Evaluation Methods for Learning About Users
Ingrid Zukerman, Ann E. Nicholson, David W. Albrecht · 1999
This paper describes the evaluation methods applied to assess the performance of the user models developed in the framework of a three-year plan recognition project. The user models were learned from observations of the behaviour of large numbers of users, and were used to predict users' immediate activities and eventual goals in two related domains: a Multi-User adventure game and the World Wide Web. The evaluation methods were influenced by the features of the domain and the applied modeling techniques. 1 Introduction Systems that learn about users typically perform the following tasks: (1) collect data, (2) consider the features of the domain to identify models that are suitable for representing the data, (3) use the data to learn the parameters (and structure) of the models, and (4) evaluate the learned models. In the last three years, we have been working on a project which involves learning user models from observations of the behaviour of large numbers of users. The ...