process may be characterized as  winnowing  the harvested URLs. Automated systems

currently used by filtering software vendors to prioritize, and to categorize or tentatively

categorize the content and/or features of a Web site or page accessed via a particular URL

operate by means of (1) simple key word searching, and (2) the use of statistical

algorithms that rely on the frequency and structure of various linguistic features in a Web

page's text.  The automated systems used to categorize pages do not include image

recognition technology.  All of the filtering companies deposed in the case also employ

human review of some or all collected Web pages at some point during the process of

categorizing Web pages.  As with the harvesting process, each technique employed in the

winnowing process is subject to limitations that can result in both overblocking and

underblocking.  

First, simple key word based filters are subject to the obvious limitation that no

string of words can identify all sites that contain sexually explicit content, and most

strings of words are likely to appear in Web sites that are not properly classified as

containing sexually explicit content.  As noted above, filtering software companies also

use more sophisticated automated classification systems for the statistical classification of

texts.  These systems assign weights to words or other textual features and use algorithms

to determine whether a text belongs to a certain category.  These algorithms sometimes

make reference to the position of a word within a text or its relative proximity to other

words.  The weights are usually determined by machine learning methods (often

described as  artificial intelligence ).  In this procedure, which resembles an automated

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