Data Mining - Concepts and Techniques.

An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

Using context information to facilitate processing of commands in a virtual assistant

An electronic device may capture a voice command from a user. The electronic device may store contextual information about the state of the electronic device when the voice command is received. The electronic device may transmit the voice command and the contextual information to computing equipment such as a desktop computer or a remote server. The computing equipment may perform a speech recognition operation on the voice command and may process the contextual information. The computing equipment may respond to the voice command. The computing equipment may also transmit information to the electronic device that allows the electronic device to respond to the voice command.

Electronic Devices with Voice Command and Contextual Data Processing Capabilities

The method includes automatically, without user input and without regard to whether a digital assistant application has been separately invoked by a user, determining that the electronic device is in a vehicle. In some implementations, determining that the electronic device is in a vehicle comprises detecting that the electronic device is in communication with the vehicle (e.g., via a wired or wireless communication techniques and/or protocols). The method also includes, responsive to the determining, invoking a listening mode of a virtual assistant implemented by the electronic device. In some implementations, the method also includes limiting the ability of a user to view visual output presented by the electronic device, provide typed input to the electronic device, and the like.

Automatically adapting user interfaces for hands-free interaction

According to a present invention embodiment, a system utilizes a voice tag to automatically tag one or more entities within a social media environment, and comprises a computer system including at least one processor. The system analyzes the voice tag to identify one or more entities, where the voice tag includes voice signals providing information pertaining to one or more entities. One or more characteristics of each identified entity are determined based on the information within the voice tag. One or more entities appropriate for tagging within the social media environment are determined based on the characteristics and user settings within the social media environment of the identified entities, and automatically tagged. Embodiments of the present invention further include a method and computer program product for utilizing a voice tag to automatically tag one or more entities within a social media environment in substantially the same manner described above.

Application of Voice Tags in a Social Media Context

The Only Complete Technical Primer for MDM Planners, Architects, and ImplementersCompanies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments.Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM data management innovators who are pioneering MDM, this book systematically introduces MDMs key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA.Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere elseeverything you need to establish a consistent, manageable set of master data, and use it for competitive advantage.Coverage includesHow MDM and SOA complement each otherUsing the MDM Reference Architecture to position and design MDM solutions within an enterpriseAssessing the value and risks to master data and applying the right security controlsUsing PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challengesExplaining MDM patterns as enablers to accelerate consistent MDM deploymentsIncorporating MDM solutions into existing IT landscapes via MDM Integration BlueprintsLeveraging master data as an enterprise assetbringing people, processes, and technology together with MDM and data governanceBest practices in MDM deployment, including data warehouse and SAP integration

Enterprise Master Data Management: An SOA Approach to Managing Core Information

A method, computer program product and system for managing tenant-specific data sets in a multi-tenant system, by receiving a request to convert a data set in a physical data store from a first type of multi-tenant deployment to a second type of multi-tenant deployment, retrieving tenant identification metadata identifying a tenant making the request, modifying the data set in the physical data store based on the second type of multi-tenant deployment, and modifying metadata associated with an abstraction layer to allow the modified data set to be accessed.

Managing tenant-specific data sets in a multi-tenant environment

A computer-implemented method for the placing of information assets, including: discovering information about a new or changed information asset; determining one or more characteristics of an ideal location for the information asset; determining one or more characteristics of one or more locations in an information technology environment; determining the compatibility of the information asset with the location(s) by comparing the characteristic(s) of the ideal location to the characteristic(s) of the actual location(s); reporting the compatibility to a user; and optionally suggesting alternative placement locations. The locations may be part of one or more locational schemas.

Information asset placer

A computer-implemented method for processing information related to an extract-transform-load (ETL) data migration, including aggregating operational metadata and determining: a plurality of metrics, organized by business object, corresponding to the migration; a number of business object instances not successfully loaded; a first end-to-end execution time for at least one business object; relevant input metadata; load readiness status per business object; impact of a business object that is not load ready by analyzing business process hierarchies; business object load readiness by reference to incomplete development status or data defects; scope per test cycle based, at least in part, upon business object load readiness; and high-priority defects of business objects that stop testing based, at least in part, upon analysis of business process hierarchies.

Martin Oberhofer

Papers

Application of Voice Tags in a Social Media Context

Enterprise Master Data Management: An SOA Approach to Managing Core Information

Managing tenant-specific data sets in a multi-tenant environment

Information asset placer

Processing data in data migration