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. 2009 Mar 11;4(3):e4803. doi: 10.1371/journal.pone.0004803

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This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

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Usage log data consists of sequences of timed interaction events . Interaction events issued by the same user from the same client can be grouped in user sessions. Each user session represents a clickstream that can be expressed as a sequence of the articles that were part of the session's interaction events, i.e. . Since every article is published in a journal, we can derive journal clickstreams, i.e. . From the collection of all journal clickstreams we can calculate the probability .

Inline graphic — Usage log data consists of sequences of timed interaction events . Interaction events issued by the same user from the same client can be grouped in user sessions. Each user session represents a clickstream that can be expressed as a sequence of the articles that were part of the session's interaction events, i.e. . Since every article is published in a journal, we can derive journal clickstreams, i.e. . From the collection of all journal clickstreams we can calculate the probability .