Predicting Information Searchers’ Topic Knowledge at Different Search Stages

Jingjing Liu

Abstract:

As a significant contextual factor in information search,
topic knowledge has been gaining increased research
attention. We report on a study of the relationship
between information searchers’ topic knowledge and
their search behaviors, and on an attempt to predict
searchers’ topic knowledge from their behaviors during
the search. Data were collected in a controlled laboratory
experiment with 32 undergraduate journalism
student participants, each searching on 4 tasks of different
types. In general, behavioral variables were not
found to have significant differences between users with
high and low levels of topic knowledge, except the mean
first dwell time on search result pages. Several models
were built to predict topic knowledge using behavioral
variables calculated at 3 different stages of search episodes:
the first-query-round, the middle point of the
search, and the end point. It was found that a model
using some search behaviors observed in the first query
round led to satisfactory prediction results. The results
suggest that early-session search behaviors can be
used to predict users’ topic knowledge levels, allowing
personalization of search for users with different levels
of topic knowledge, especially in order to assist users
with low topic knowledge.