20,055 research outputs found
Mutual information based clustering of market basket data for profiling users
Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This contribution shows for the example of a cooking information site how user profiles might be obtained using category information provided by cooking recipes. It is shown that metrical distance functions and standard clustering procedures lead to erroneous results. Instead, we propose a new mutual information based clustering approach and outline its implications for the example of user profiling
Patterns of trading profiles at the Nordic Stock Exchange. A correlation-based approach
We investigate the trading behavior of Finnish individual investors trading
the stocks selected to compute the OMXH25 index in 2003 by tracking the
individual daily investment decisions. We verify that the set of investors is a
highly heterogeneous system under many aspects. We introduce a correlation
based method that is able to detect a hierarchical structure of the trading
profiles of heterogeneous individual investors. We verify that the detected
hierarchical structure is highly overlapping with the cluster structure
obtained with the approach of statistically validated networks when an
appropriate threshold of the hierarchical trees is used. We also show that the
combination of the correlation based method and of the statistically validated
method provides a way to expand the information about the clusters of investors
with similar trading profiles in a robust and reliable way.Comment: 25 pages, 8 figure
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