Dynamic rule allocation for visitor identification

A computerized method for identifying a website visitor, the computerized method comprising:

• receiving, via a first computing process performed at a server device, a set of log data for a website from a web server device, the set of log data including cookies and an identification of a website visitor corresponding to each cookie;
• computing, via a second computing process performed at the server device, a cookie representation for each cookie under a numeric vector space, the cookie representation being computed using cookie statistics including a frequency of hits in the log data;
• evaluating, via a third computing process preformed at the server device, cookie-stitching rules from a set of cookie-stitching rules by applying each cookie-stitching rule from the set of cookie-stitching rules to the cookie representations to determine an effectiveness score for each cookie-stitching rule;
• training, via a fourth computing process performed at the server device, a classifier of effectiveness scores for each cookie-stitching rule of the set of cookie-stitching rules, each effectiveness score being a measurement of the effectiveness of each cookie-stitching rule at identifying website visitors based on the cookie representation and comprising a binary-classification evaluation metric;
• and
• utilizing, via a fifth computing process performed at the server device, the classifier to select a most effective cookie-stitching rule for log data corresponding to an unknown website visitor, the most effective cookie-stitching rule being a cookie-stitching rule with the highest cookie-stitching effectiveness score relative to other cookie-stitching rules from the set of cookie-stitching rules, wherein the highest effectiveness score comprises a highest binary-classification evaluation metric.

A computerized system comprising:

• a processor;
• and
• a non-transitory computer storage media storing computer-useable instructions that, when used by the processor, cause the processor to:
• predict effectiveness scores for each cookie-stitching rule in a set of cookie-stitching rules for a cookie representation, the cookie representation being computed using cookie statistics including a frequency of hits in log data, the effectiveness scores being predicted by applying each cookie-stitching rule to a cookie representation, wherein each effectiveness score measuring measures an effectiveness for identifying cookies with cookie representations similar to the cookie representation and comprises a binary-classification evaluation metric;
• select, from the set of cookie-stitching rules, the cookie-stitching rule with a highest effectiveness score, the highest effectiveness score comprising a highest binary-classification evaluation metric and indicating that the cookie-stitching rule is most effective, relative to other cookie-stitching rules within the set, at identifying website visitors associated with cookies with similar cookie representations to the cookie representation;
• and
• apply the cookie-stitching rule to a received cookie to identify an unknown website visitor associated with the received cookie.