International Business Machines Corporation

Nuance Communications, Inc.

Stephen Carl Gates

Wilfried Teiken

Youngja Park

Lawrence H Koved

Pau-Chen Cheng

Roy Jefferson Byrd

Mary Susan Neff

Suresh N Chari

Christopher Gates

Michael E Moran

Alexander Wolcott Holt

Pat Velderman

Philip Shi-lung Yu

Charu Chandra Aggarwal

Josyula R Rao

Keh-Shin Fu Cheng

Automatically estimating a sensitivity level of an information technology (IT) asset in one aspect may obtain information about an asset. Characteristics of the asset assigned based on the information may be compared with stored characteristics of known sensitive assets. A sensitivity level of the asset may be determined based on the comparing.

Estimating asset sensitivity using information associated with users

Systems and methods for protecting a data item include, upon initiation of transfer of the data item from a server to a client device, determining a sensitivity score and a current protection, level of the data item. A policy is applied to determine an appropriate protection for the data item based upon the sensitivity score and the current protection level. A protected data item is provided to the client device by applying the appropriate protection to the data item.

System and method to provide server control for access to mobile client data

Systems and methods for protecting a data item include, upon initiation of transfer of the data item from a server to a client device, determining a sensitivity score and a current protection level of the data item. A policy is applied to determine an appropriate protection for the data item based upon the sensitivity score and the current protection level. A protected data item is provided to the client device by applying the appropriate protection to the data item.

A system and method for providing an adaptive Interaction Logging functionality to help agents reduce the time spent documenting contact center interactions. In a preferred embodiment the system uses a pipeline comprising audio capture of a telephone conversation, automatic speech transcription, text normalization, transcript generation and candidate call log generation based on Real-time and Global Models. The contact center agent edits the candidate call log to create the final call log. The models are updated based on analysis of user feedback in the form of the editing of the candidate call log done by the contact center agents or supervisors. The pipeline yields a candidate call log which the agents can edit in less time than it would take them to generate a call log manually.

System and method for automatically generating adaptive interaction logs from customer interaction text

Techniques for limiting the risk of loss of sensitive data from a mobile device are provided. In one aspect, a method for managing sensitive data on a mobile device is provided. The method includes the following steps. A sensitivity of a data item to be transferred to the mobile device is determined. It is determined whether an aggregate sensitivity of data items already present on the mobile device plus the data item to be transferred exceeds a current threshold sensitivity value for the mobile device. If the aggregate sensitivity exceeds the current threshold sensitivity value, measures are employed to ensure the aggregate sensitivity remains below the current threshold sensitivity value for the mobile device. Otherwise the data item is transferred to the mobile device.

System and method to govern sensitive data exchange with mobile devices based on threshold sensitivity values

A real-time method and system are described for automatically extracting text from the customer-agent interaction at a contact center, analyzing the extracted text to automatically identify one or more customer issues, and performing processing by contact-center agent buddies (CABs) to generate at least one response to the customer issues.

System and method for real time support for agents in contact center environments

Methods, apparatus and systems are provided to generate from a set of training documents a set of training data and a set of features for a taxonomy of categories. In this generated taxonomy the degree of feature overlap among categories is minimized in order to optimize use with a machine-based categorizer. However, the categories still make sense to a human because a human makes the decisions regarding category definitions. In an example embodiment, for each category, a plurality of training documents selected using Web search engines is generated, the documents winnowed to produce a more refined set of training documents, and a set of features highly differentiating for that category within a set of categories (a supercategory) extracted. This set of training documents or differentiating features is used as input to a categorizer, which determines for a plurality of test documents the plurality of categories to which they best belong.

Creating taxonomies and training data for document categorization

A system and computer readable medium for providing a set of refinement categories for a set of search results generated in response to a search query. The system comprises: a category identifier system that analyzes each search result and identifies at least one category from a hierarchy of categories for each search result, thereby providing a list of identified categories; a ranking system that ranks each category in the list of identified categories; and a selection system that selects a predetermined number of the highest ranking categories from the list of identified categories to generate the set of refinement categories, wherein the selection system eliminates categories from the set of refinement categories if the category has a parent in the set of refinement categories.

System and computer readable medium for generating refinement categories for a set of search results

A system for enhancing search results generated in response to a search query. The system comprises: a category identifier system that analyzes each search result and identifies at least one category from a hierarchy of categories for each search result, thereby providing a list of identified categories; a ranking system that ranks each category in the list of identified categories; and a selection system that selects a predetermined number of the highest ranking categories from the list of identified categories to generate the set of refinement categories, wherein the selection system eliminates categories from the set of refinement categories if the category has a parent in the set of refinement categories.

System and method for generating refinement categories for a set of search results

Methods, apparatus and systems to generate from a set of training documents a set of training data and a set of features for a taxonomy of categories. In this generated taxonomy the degree of feature overlap among categories is minimized in order to optimize use with a machine-based categorizer. However, the categories still make sense to a human because a human makes the decisions regarding category definitions. In an example embodiment, for each category, a plurality of training documents selected using Web search engines is generated, the documents winnowed to produce a more refined set of training documents, and a set of features highly differentiating for that category within a set of categories (a supercategory) extracted. This set of training documents or differentiating features is used as input to a categorizer, which determines for a plurality of test documents the plurality of categories to which they best belong.

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Redding, CT, United States of America

Stephen Carl Gates