5. The Internet searching application method as recited in claim 1 , wherein the user-trainable predictive analytical model comprises at least one of a support vector network, a support vector machine, a machine learning mechanism and a neural network, the user-trainable predictive analytical model further configured to suggest a plurality of websites responsive to the user query based on the user's browsing history data, search history data, and historical data relating to previous deletions of suggested websites by the user.
1. An Internet searching application method, comprising: receiving a user query with respect to an Internet searching session established at a user equipment (UE) device; determining search results responsive to the user query based on a user-trainable predictive analytical model, the search results including websites relevant to the user query, wherein relevance is predicted responsive to pair-wise comparisons between websites classified into multiple classes; providing the search results for presentation via a user interface displayed at the UE device; receiving a user interaction response comprising at least one of deleting a particular search result based on the user's perception of whether the particular search result is relevant to the user query; and utilizing the user interaction response as an input to a training machine used in association with the predictive analytical model, wherein the user interaction response is used at least in part in selecting a classifier variable for classifying websites into the multiple classes, thereby modulating predictive behavior of the predictive analytical model with respect to future searching sessions of the user.