Designing human-readable user profiles for search evaluation

Authors:
Carsten Eickhoff;Kevyn Collins-Thompson;Paul Bennett;Susan Dumais
Affiliations:
Delft University of Technology, Delft, The Netherlands;Microsoft Research, Redmond;Microsoft Research, Redmond;Microsoft Research, Redmond
Venue:
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Year:
2013

Citing 6
Cited 1

Measures of relative relevance and ranked half-life: performance indicators for interactive IR

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
User Profile Modeling and Applications to Digital Libraries

ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
Building and applying a concept hierarchy representation of a user profile

Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Personalizing search via automated analysis of interests and activities

Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Classification-enhanced ranking

Proceedings of the 19th international conference on World wide web
Personalizing web search results by reading level

Proceedings of the 20th ACM international conference on Information and knowledge management

Personalizing atypical web search sessions

Proceedings of the sixth ACM international conference on Web search and data mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

Forming an accurate mental model of a user is crucial for the qualitative design and evaluation steps of many information-centric applications such as web search, content recommendation, or advertising. This process can often be time-consuming as search and interaction histories become verbose. In this work, we present and analyze the usefulness of concise human-readable user profiles in order to enhance system tuning and evaluation by means of user studies.