Novell, Inc.

Micro Focus Software Inc.

Apple Inc.

Oracle International Corporation

Novell Intellectual Property Holdings, Inc.

Scott Alan Isaacson

Stephen R Carter

Tammy Anita Green

Nadeem Ahmad Nazeer

Craig N Teerlink

Alexander Y Danoyan

Kirk R Kimball

Robert A Wipfel

Eric W B Anderson

Andrew Fox

Haripriya Srinivasaraghavan

David Marshall LaPalomento

Ian Edward Roughley

Allan W Neill

Larry Hal Henderson

Daniel Gene Fritch

Lynn Wells Crabb

James Duane Nyland, Jr

William Street

Ravi Kumar

Kattiganehalli Y Srinivasan

Michel Shane Simpson

Ashish Anant Vaidya

John Melvin Antony

Nathan Blaine Jensen

Ranjan Gupta

Kenneth W Muir

Kevin Marinus Boogert

Jim Alan Nicolet

James Bart Whiteley

Jon Carey

David Reveman

Jeffrey Todd Hawkins

Jason Taylor

Anna Dirks

Daniel C Lawyer

Matthew Richard French

William Robert Whitehead, Jr

Nithya Balachandran

R Shyamsundar

Frank Allan Nutt

Kyrt V Nay

Mandhakini Subramanian

Thomas J Brough

Manoj Madhavan

Pooja Gada

James D Nyland, Jr

Bradley Garrell Nicholes

William D Peterson

Brett D Garrett

Jim A Nicolet

Eric Anderson

Eric B Anderson

Methods and apparatus teach providing semantic associations between data available on one or more computing devices, including grouping together related files and creating an association between the related grouped files and at least one anchor file to provide a semantic association for the grouped files. Also is taught configuring an agent on the one or more computing devices to undertake the grouping and to create the association without a user request. Also is taught triggering an evaluation of current files against related grouped files, and creating an association between the current files and at least one of the related grouped files and the at least one anchor file. Information may be added to the created association to create additional semantic associations for one or more of the grouped files and the current files. In turn, computer program products and computing systems for accomplishing the foregoing are provided.

Semantic associations in data

Techniques for meta-directory control and evaluation of events are provided. Disparate events from heterogeneous processing environments are collected as the events are produced by resources within the processing environments. The events are filtered and organized into taxonomies. Next the filtered and organized events are assigned to nodes of a Meta directory, each node defining a relationship between two or more of the resources and policy is applied. Finally, additional policy is evaluated in view of the events and their node assignments with other events, and one or more automated actions are then taken.

Meta-directory control and evaluation of events

A machine-controlled method may include receiving a file in a designated shared folder on a local device, automatically providing access to the file to a social networking website or service, and directing the social networking website or service to make the file available to users that are allowed to access a particular user account at the social networking website.

Social networking content management

Method and system for presenting a view of a calendar on an electronic display. In one embodiment, the method comprises presenting on the display an entry corresponding to a scheduled meeting having at least two participants; presenting on the display a first timeline associated with a first one of the participants, the first timeline comprising an incremental listing of time of day in accordance with a first time zone; presenting on the display a second timeline adjacent the first timeline, the second timeline associated with a second one of the participants and comprising an incremental listing of time of day in accordance with a second time zone; and wherein the entry is presented on the display relative to the first and second timelines to thereby reflect start and end times of the scheduled meeting relative to each of the first and second time zones.

System and method for displaying multiple time zones in an online calendar view

A swarm can develop around a piece of content. The swarm can include the original content, changes to the original content, the persons contributing the changes, and metadata, such as comments contributed by members of the swarm. A swarm can also include statistics generated about the content, such as the size of the swarm, the growth and/or death rates of the swarm, the longevity of the swarm, the intensity of the swarm, the persistence of the swarm, and the direction of the swarm. Swarms and their behaviors can be used to validate or invalidate content.

Collaboration swarming

An application can receive a request to insert one file into another file opened for editing within the application. The request can be either in-line or through a menu system of the application. The request can include a context for the file to be inserted. The system can then identify a set of files that can satisfy the context, from which a user can choose what file is to be inserted. The chosen file can then be inserted into the file opened for editing, all without leaving the application.

Integrated media browse and insertion

Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together, while others are differentiated. Grouping ceases upon application of a stopping function so that rightly sized, optimum numbers of file groups are obtained. Embodiments of stopping functions relate to curve types in a mapping of numbers of groups per sequential rounds of grouping, recognizing whether groups have overlapping file members or not, and/or determining whether groups meet predetermined numbers of members, to name a few. Properly grouped files can then be further acted upon.

Stopping functions for grouping and differentiating files based on content

Methods and apparatus teach a digital spectrum of a file representing underlying original data. The digital spectrum is used to map a file's position. This position relative to another file's position reveals closest neighbors. When multiple such neighbors are grouped together they can be used to indicate relevance in current data under consideration on a same or different computing device. Also, relevance can be found without traditional notions of needing structured data or users initiating searching for relevance or by examining metadata/administrative information associated with the files. A dynamic relevancy agent is configured for installation on the same or different computing device to monitor events regarding the current data and to initiate the examination of relevancy. It also presents to a user suggestions of data closest to the current data. Various triggering events to undertake a relevancy examination are also described as are predetermined criteria to define relative closeness.

Harvesting relevancy data, including dynamic relevancy agent based on underlying grouped and differentiated files

A machine receives a description of the relationships among members of a data set. The machine constructs a graph that represents the relationships among the members of the data set, organizing the members of the data set into groups. The groups are analyzed to determine their relative strengths. Unbalanced groups can be balanced by splitting off heavy sub-trees that include too large a percentage of the nodes in the group. The machine can then use the graph to answer queries about members of the data set.

Structured relevance&#x2014;a mechanism to reveal how data is related

A machine receives a group of members of a data set. The machine identifies key symbols from the members of the group or the data set. The machine then calculates, for each key symbol, a weighted magnitude for the key symbol in the group. The machine can then sort the key symbols according to their weighted magnitudes, and filter out common key symbols. The uncommon key symbols, as sorted according to their weighted magnitudes, can form a name for the group.

Structured relevance&#x2014;a mechanism to reveal why data is related

Methods and computer program product relate to user input auto-completion. The methods and product are executable on a processing device in a computing system environment so as to provide an auto-completion scheme with enhanced capabilities that improve user efficiency when performing a task.

User input auto-completion

Techniques for collaborative decision making are presented. A collaborative decision making process is referred to as a buzz. A principal creates and defines the policies for the buzz as well as the criteria for participants of the buzz. The buzz is launched for online collaboration and is managed according to the policies. Actions and decisions are logged and recorded during the buzz.

Collaborative decision making

Techniques for content services are provided. Documents are managed from their native storage locations. Access to portions of the documents is provided via separate addressable references. Principals access and annotate the portions of the documents remotely. Identity and policy restrictions are enforced against access from the native storage locations.

Techniques for content services

Techniques for enabling storage remotely are presented. A REpresentational State Transfer (REST) front-end interface is interfaced to a legacy file system via a backend interface that directly interacts with the native storage and protocols of the legacy file system. The REST interface is presented as the frontend interface to the legacy file system making the storage of the legacy file system available to web or network-enabled devices.

Remote enabling of storage

Techniques for trusted platform module (TPM) assisted data center management are provided. A data center registers TPM remote attestations for physical processing environments of physical devices within a data center. Each time a physical processing environment is established; a new TPM remote attestation is generated and validated against the registered TPM remote attestation. Additionally, during registration other identifying information is supplied to the physical processing environments that permit each physical processing environment to be authenticated, validated, and controlled via unique identities. Inter-data center communication is established for sharing virtual processing environments and administrative operations are authenticated within each of the data centers perform any administrative operation is permitted to process within a particular data center.

Trusted platform module (TPM) assisted data center management

Growing community of inventors

Woodland Hills, UT, United States of America

Scott Alan Isaacson