Patent application number | Description | Published |
20090204599 | USING RELATED USERS DATA TO ENHANCE WEB SEARCH - The claimed subject matter provides a system and/or a method that facilitates generating a personalized query result for a specific user. An interface can receive at least one of a portion of a text query to be searched or a portion of personalized content related to a user that submits the portion of the text query. A personalization component can combine the portion of personalized content related to the user with a portion of personalized content related to one or more disparate users to create group personalized content, wherein the group personalized content is compared with the portion of the text query to identify a relationship there between to generate a personalized query result in accordance with the relationship. | 08-13-2009 |
20090204902 | SYSTEM AND INTERFACE FOR CO-LOCATED COLLABORATIVE WEB SEARCH - Systems and methods are provided to perform collaborative retrieval, communication, and navigation of electronic content in a co-located environment. In an illustrative implementation, a collaborative content environment comprises a collaborative content interface engine, and an instruction set comprising at least one instruction providing instructions to the collaborative content interface engine to process data representative of inputs from two or more cooperating interface devices to allow for the retrieval, communication, search, and navigation of electronic content. In the illustrative implementation, the collaborative content interface engine can present retrieved, communicated, searched, and/or navigated data according to a selected display paradigm. The display paradigm can include one or more display portions of a display pane comprising data responsive to the inputs received from the two or more cooperating interface devices. | 08-13-2009 |
20100325572 | MULTIPLE MOUSE CHARACTER ENTRY - This document relates to multiple mouse character entry. More particularly, the document relates to multiple mouse character entry tools for use on a common or shared graphical user interface (GUI). In some implementations, the multiple mouse character entry tools (MMCE tools) can generate a GUI that includes multiple distinctively identified cursors. Individual cursors can be controlled by individual users via a corresponding mouse. The MMCE tools can associate a set of characters with an individual cursor effective that an individual user can use the mouse's scroll wheel to scroll to specific characters of the set. The user can select an individual character by clicking a button of the mouse. | 12-23-2010 |
20120239596 | CLASSIFICATION OF STREAM-BASED DATA USING MACHINE LEARNING - The described implementations relate to data classification. One implementation includes identifying one or more likely classifications for an incoming data item using an algorithm. The implementation can also include providing the one or more identified classifications to a user. A selection of an individual identified classification for the incoming data item can be received from the user. The algorithm can be refined to reflect the selection by the user. | 09-20-2012 |
Patent application number | Description | Published |
20130055268 | AUTOMATED WEB TASK PROCEDURES BASED ON AN ANALYSIS OF ACTIONS IN WEB BROWSING HISTORY LOGS - Embodiments of the invention relate to generating automated web task procedures from an analysis of web history logs. One aspect of the invention concerns a method that comprises identifying sequences of related web actions from a web log, grouping each set of similar web actions into an action class, and mapping the sequences of related web actions into sequences of action classes. The method further clusters each group of similar sequences of action classes into a cluster, wherein relationships among the action classes in the cluster are represented by a state machine, and generates automated web task procedures from the state machine. | 02-28-2013 |
20140019979 | AUTOMATED WEB TASK PROCEDURES BASED ON AN ANALYSIS OF ACTIONS IN WEB BROWSING HISTORY LOGS - Embodiments of the invention relate to generating automated web task procedures from an analysis of web history logs. One aspect of the invention concerns a method that comprises identifying sequences of related web actions from a web log, grouping each set of similar web actions into an action class, and mapping the sequences of related web actions into sequences of action classes. The method further clusters each group of similar sequences of action classes into a cluster, wherein relationships among the action classes in the cluster are represented by a state machine, and generates automated web task procedures from the state machine. | 01-16-2014 |
20150019211 | INTERACTIVE CONCEPT EDITING IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
20150019461 | INTERACTIVE SEGMENT EXTRACTION IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
20150019463 | ACTIVE FEATURING IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |