Abstract: Methods and systems are described for a method that enables the examining of user behavior while viewing content on the Internet. The collection and analysis of user behavior heuristics can be very useful in determining a user's interests and can be used in delivering more targeted ads to the user. JavaScript is embedded in an ad that is delivered to a Web site that a user is visiting. The JavaScript is used to collect data on how the user is behaving on the Web site. It measures heuristics such as “blur” and “focus” which provide a detailed analysis of a user's viewing habits. These heuristics can indicate how often a user scrolls through content, minimizes/maximizes windows, flips among various applications (e.g. e-mail, reading content, instant messaging, etc.) among numerous other user actions. By examining these habits and other behavior, it is possible to gain more insight into what type of content a user is interested in.

Abstract: Methods and systems are described for real time, targeted, contextual ad serving in a multilingual online environment. Upon receiving a request for serving an ad to a non-English Web site, an ad server obtains non-English content from the particular Web site page and has it translated to English. The English version of the content is input to an English language classifier, which has been developed extensively and has voluminous training sets for numerous topics. The results from the classification are translated to the non-English language and used by the ad server to select an appropriate contextual, targeted ad to be delivered to the non-English Web site. Special techniques are used in the classification process wherein classification results, which may be a list of topics with associated relevancy weights, are better suited for selecting a contextual ad in real time for the non-English Web site.