of User Interactions with Data-intensive Systems by Modeling
of User Communication Style, Temperament, and Preferences by Anne Y.A. Chen
web-search engines provide query results with relatively high
precision and recall, but user satisfaction is often low.
Precision and recall are two traditional measurements of data
accuracy but not user satisfaction and preferences. Therefore,
user characteristics and preferences have become important
in information retrieval. Modeling users' temperaments provides
a base for an information recommendation service. We incorporate
human temperaments into the filtering process via Keirsey's
temperament theory, probability theory, and statistical reasoning.
The system providing recommendation services searches information
taking into account user temperament (communication style).
According to Keirsey's theory, there are four types of temperaments
which identify users' inner personalities. These are SJ (Sensing
and Judging), SP (Sensing and Perceiving), NT (iNtuition and
Thinking) and NF (Intuition and Feeling). We find correlations
between user temperaments and user preferences, which provides
a general foundation for our content-based filtering recommendation
many recommendation systems are designed to provide personalized
query results to match user preferences in order to increase
user satisfaction, none of these systems was designed to interpret
the semantic meaning of user queries and match it with semantic
information of the data. The goal of our research is to test
the hypothesis that a semantics-based system incorporating
ontologies can provide personalized query results that match
user preferences and increase user satisfaction. A system
is being developed to examine the effects of customized information
retrieval. This semantics-based system consists of six components:
query processor, query generation, user information collector,
user profile manager, result refinement, and ontology management.
The information in ontologies was incorporated into the information
process functioning of every component in the system. The
user information collector and user profile manager compile
user information and analyze that information based on the
ontologies. Information in a user profile is applied in order
to provide customized result presentations that match user
preferences. The semantics-based customization can be associated
with online search engines, online shopping sites, and other
web service information providers.
Sponsors & Affiliates |
© 2000-2013 Semantic Information Research Laboratory. All Rights Reserved.