Automatic client-side user-behavior analysis for inferring user intent

Abstract

User intent may be inferred from mouse movements made within a user interface. Client-side instrumentation may be provided that collects mouse movement data that is provided to a classification engine. The classification engine receives the mouse movement data and creates a mouse trajectory. The mouse trajectory may be split into segments, and features associated with each segment may be determined. Features representing the context of the search, that is, content of the search result page, previous queries submitted, and interaction features such as scrolling, may be included. By examining the features associated with the mouse trajectories within the context of a search session, the user intent may be classified into categories using machine learning classification techniques. By inferring user intent, Web search engines may be able to predict whether a user's intent is commercial and tailor advertising accordingly.