User-Trained Searching Application System and Method

摘要

System, apparatus, user equipment, and associated computer program and computing methods are provided for suggesting websites that are relevant based on the user's browsing history and past search results. In one aspect, a hosted computer application stores the user's browsing history and search results using a cloud-based storage facility, and computing methods, using machine learning techniques, are operative to predict websites the user may want to visit next. Example machine learning techniques may be configured to use non-parsed and unstructured data to identify patterns and map hundreds of thousands of data elements, to predict which website(s) the user might like to visit in a search/browsing session. Example machine learning techniques may be further operative to recognize patterns and analyze data at each interaction with the user. The training of example machine learning techniques is driven by user interaction, allowing the removal of non-relevant or less relevant websites from the suggested websites via a suitable user interface.

主权项

1. An Internet searching application method, comprising:
receiving a user input with respect to an Internet searching session established at a user equipment (UE) device; determining search results responsive to the user input based on a predictive analytical model; presenting the search results in a visualization format to be displayed at the UE device; receiving a user interaction response comprising at least one of deleting a search result from the visualization format; and utilizing the user interaction response as an input to a training machine used in association with the predictive analytical model, thereby modulating predictive behavior of the predictive analytical model with respect to future searching sessions of the user.