Term extraction for user profiling: Evaluation by the user
conference paper
We compared three term scoring methods in their ability to extract descriptive terms from a knowledge worker's document collection. We compared the methods in two different evaluation scenarios, both from the perspective of the user: a perterm evaluation, and a holistic (term cloud) evaluation. We found that users tend to prefer a term scoring method that gives a higher score to multi-word terms than to single-word terms. In addition, users are not always consistent in their judgements of term profiles, if they are presented in different forms (as list or as cloud).
Topics
TNO Identifier
524063
Publisher
CEUR-WS
Source title
Late-Breaking Results, Project Papers and Workshop Proceedings of the 21st Conference on User Modeling, Adaptation, and Personalization, Rome, Italy, June 10-14, 2013
Editor(s)
Santos, O.C.
Lops, P.
Berkovsky, S.
Herder E.
Lops, P.
Berkovsky, S.
Herder E.