Abstract: A system and method for generating feature vectors of documents in different languages are provided. The feature vectors provide scores associated with keywords defined in a base language for use by a profiler for generating or updating a user profile. The system and method use a plurality of keyword sets comprising: a base language keyword set comprising a plurality of base language keywords each associated with a respective identifier (ID); and a second language keyword set comprising a plurality of second language keywords each corresponding in meaning to a respective one of the base language keywords and associated with the ID of the corresponding base language keyword. One of a plurality of tokenizers is selected to parse a document based on the language of the document and to generate the feature vector using the keyword set of the corresponding language.

Abstract: The present invention relates to a method and apparatus for assisting with automated task management. In one embodiment, an apparatus for assisting a user in the execution of a task, where the task includes one or more workflows required to accomplish a goal defined by the user, includes a task learner for creating new workflows from user demonstrations, a workflow tracker for identifying and tracking the progress of a current workflow executing on a machine used by the user, a task assistance processor coupled to the workflow tracker, for generating a suggestion based on the progress of the current workflow, and a task executor coupled to the task assistance processor, for manipulating an application on the machine used by the user to carry out the suggestion.

Abstract: A method for categorization using multiple categories including obtaining multiple uniform resource locators (URLs) associated with the multiple categories, collecting multiple web pages identified by the multiple URLs, generating vocabulary terms based on the multiple web pages, generating an N-gram file including the multiple vocabulary terms, generating multiple classified URLs by labeling the plurality of URLs based on the multiple categories, generating multiple feature vectors by processing the classified URLs and the multiple web pages against the N-gram file, generating a categorization model by applying a machine learning algorithm to the multiple feature vectors, and loading a classifier with the categorization module and the N-gram file.

Abstract: A system and method for generating feature vectors of documents in different languages are provided. The feature vectors provide scores associated with keywords defined in a base language for use by a profiler for generating or updating a user profile. The system and method use a plurality of keyword sets comprising: a base language keyword set comprising a plurality of base language keywords each associated with a respective identifier (ID); and a second language keyword set comprising a plurality of second language keywords each corresponding in meaning to a respective one of the base language keywords and associated with the ID of the corresponding base language keyword. One of a plurality of tokenizers is selected to parse a document based on the language of the document and to generate the feature vector using the keyword set of the corresponding language.

Abstract: A method for categorization using multiple categories including obtaining multiple uniform resource locators (URLs) associated with the multiple categories, collecting multiple web pages identified by the multiple URLs, generating vocabulary terms based on the multiple web pages, generating an N-gram file including the multiple vocabulary terms, generating multiple classified URLs by labeling the plurality of URLs based on the multiple categories, generating multiple feature vectors by processing the classified URLs and the multiple web pages against the N-gram file, generating a categorization model by applying a machine learning algorithm to the multiple feature vectors, and loading a classifier with the categorization module and the N-gram file.

Abstract: A method for generating a behavioral model for a targeted advertisement category (TAC), including: obtaining click stream data including ad-clicks and events preceding the ad-clicks and performed on web pages; assigning features having categories and keywords associated with the web pages to the events; identifying an ad-click of the ad-clicks and a subset of the events preceding the ad-click that result in the ad-click, where the subset of the events is associated with at least one feature; generating an aggregated event sequence by aggregating the ad-click and the subset of the events; selecting, in response to the at least one feature being associated with the TAC, a training data set including at least the aggregated event sequence; generating the behavioral model for the TAC by applying a learning algorithm to a portion of the training data set; and evaluating performance of built models and select model based on performance result.

Abstract: The present invention relates to a method and apparatus for assisting with automated task management. In one embodiment, an apparatus for assisting a user in the execution of a task, where the task includes one or more workflows required to accomplish a goal defined by the user, includes a task learner for creating new workflows from user demonstrations, a workflow tracker for identifying and tracking the progress of a current workflow executing on a machine used by the user, a task assistance processor coupled to the workflow tracker, for generating a suggestion based on the progress of the current workflow, and a task executor coupled to the task assistance processor, for manipulating an application on the machine used by the user to carry out the suggestion.