Avaya Inc.

Other

Avaya Technology LLC

Krishna Kishore Dhara

Venkatesh Krishnaswamy

Xiaotao Wu

John F Buford

Eunsoo Shim

Rajeshwari Edamadaka

Mario Kolberg

Timothy Ian Ross

Jack Iu

Michael Vernick

David Skiba

Ratan Bajpai

Anil Jwalanna

Venkatesh Krisnaswamy

Vikranth Babu Tirumalachetty

Rudra Kant

Venkat R Goud

Gary Hildebrand

Disclosed herein are systems, methods, and computer-readable storage media for authorizing third-party profile data sharing. The system receives a request to a request to share profile data held by a first person with a second person, wherein the profile data is of a third person. The system then generates a common context value based on an association between at least two of the first person, the second person, and the third person, wherein the common context value indicates how strongly the third person is connected to the first person and/or the second person. When the common context value is above a threshold, the system permits the first person to share the profile data of the third person with the second person.

System and method for authorizing third party profile data sharing

Negotiation of a future communication through a personal virtual assistant is provided. A trigger command is received. The trigger command identifies a communication received for a recipient from a sender. Schedule information is accessed. The schedule information is related to the recipient of the received communication. A plurality of options is presented to the sender. The plurality of options are for arranging a future communication between the sender and the recipient, and include at least one option determined based on the accessed schedule information. A selection of an option for arranging a future communication is received. The selected option is executed to arrange the future communication.

Negotiation of a future communication by use of a personal virtual assistant (PVA)

Disclosed herein are systems, methods, and computer-readable storage device for managing message threads. An example system configured to practice this method can first identify a usage pattern of a user interacting with a message thread. Next, based on that usage pattern, the system can analyze messages in the message thread to identify a high-priority message. Then the system highlights the high-priority message when the system renders the message thread on a display. The messages can be email messages, text messages, instant messages, etc. The system can further associate the high-priority message with a repository, and grant a repository user, access to the high-priority message.

System and method of message thread management

In one exemplary aspect, a method includes the step of obtaining a content of a content block. The content is represented as a content vector. A query is received. The query is represented as a query vector. A hierarchical sliding similarity and dissimilarity is determined for matching the content vector and the query vector, this step can include the steps of: determining a similarity measure and a dissimilarity measure for each content vector element with respect to the query vector; identifying a strong match over a sliding window of sub-terms of each content vector element; computing a sub-similarity score and a sub-dissimilarity score for each level of the convent vector element; determining a final similarity score as a combination of the strong match of some sub-vectors at different levels; and determining a final dissimilarity score as a combination of the strong match of some sub-vectors at different levels.

Method and system of identifying relevant content snippets that include additional information

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for generating a context-based rich communication log. A system configured to practice the method performs a context-based analysis of a history of communication sessions over at least two communication modalities, wherein the context-based analysis considers semantic meaning, temporal relationship, and user activities. The system generates associations between the communication sessions based on the context-based analysis, and generates the context-based rich communication log based on the associations. The context-based analysis can be based on time, session participant identifications, ongoing events, and/or on-demand queries of the communication sessions. The system can then present the context-based rich communication log to a user. The context-based rich communication log can be used as part of at least one of a predictive contacts application, a topic analyzer, a conferencing application, and a personal communication assistant, for example.

System and method for a context-based rich communication log

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for predicting the subject, logistics, and resources of associated with a communication event. Predictions and suggestions can occur prior to, during, or in response to communication events. The user can confirm the prediction or suggestion via user input such as a click or a voice command. The system can analyze past behavior patterns with respect to the subject, logistics and resources of communication events, followed by preparing ranked listings of which subjects, logistics, and resources are most likely to be used in a given situation. The predicted logistics may then include people to invite, time and date of the meeting, its duration, location, and anything else useful in helping potential participants gather together. The resources may include files attached, files used, communication event minutes, recordings made, Internet browsers and other programs which may be utilized by the user.

System and method for predicting meeting subjects, logistics, and resources

A method is provided for detecting interactions between call-related and web-enabled features. In some embodiments, communication application components are configured to transmit an indication to a feature interaction detector every time a feature is invoked by the user. When the interaction detector receives an indication that a feature is being invoked, it compares the invoked feature against features that have previously been invoked (or executed) and determines whether the invoked feature interacts with any of the features that have been previously executed.

Interaction detection between web-enabled and call-related features

Techniques for detecting and resolving feature interactions during calls are disclosed. In particular, a finite-state machine and a corresponding method detect when a feature that is invoked during a call would interact with another previously-activated feature, and ensure that both features are not active simultaneously. Three different techniques for resolution are disclosed: in one technique, activation of the latter feature is always refused; in a second technique, the former feature is always deactivated and the latter feature is then activated; and in a third technique, one of the two features is selected to be the active feature&#x2014;perhaps based on priorities assigned to the features&#x2014;and the features are activated and/or deactivated accordingly.

Mid-call detection and resolution of feature interactions

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for identifying document topics. A system configured to practice the method receives a document from a corpus of documents, learns interpersonal relationships of users associated with the document, performs a lexical analysis of the document, and, based on the interpersonal relationships of the users and the lexical analysis, identifying a topic for the document. The approaches disclosed herein can integrate user-people relationships to identify topics for documents with low lexical or high contextual content. The system can learn this user-people relationship from context. The system uses this learned behavior to identify communication documents correctly. Another aspect is the separation of the two phases. The system overlays the learned model on the lexical topic analysis, allowing the system to capture user-defined topics and user behavior that is learned from other factors such as medium (calls, events, etc) or user preferences.

System and method for classifying communications that have low lexical content and/or high contextual content into groups using topics

An application-layer multicast-based (ALM-based), peer-to-peer conferencing system is disclosed that leverages the differing capabilities of the participating peer nodes. A conference call can be set up among peer nodes of three different types. A bridging node is capable of mixing individual audio signals that are associated with a call into a composite audio signal and of providing the composite audio signal to another node. A mixing-capable node is capable of mixing the individual audio signals that are associated with a call, but not of relaying those signals to another node. A mixing-incapable node does not support the mixing of individual audio signals. The conferencing architecture of the illustrative embodiment is able to account for the differences between the three types of nodes that are to participate in a conference call, resulting in an optimal allocation of bandwidth and processing resources.

Enhanced application-layer multicast for peer-to-peer conferencing

Methods and apparatus are disclosed for providing customer treatment information over a network. A transaction communication is established between a first enterprise and a second enterprise by receiving a request from a user associated with the first enterprise to establish the transaction communication; determining if the second enterprise is authorized to access enterprise information of the first enterprise; obtaining enterprise information from an enterprise database of the first enterprise; and providing the obtained information to the second enterprise as part of the establishment of the transaction communication if the second enterprise is authorized to access the enterprise information of the first enterprise. The enterprise information is typically related to the transaction and may comprise one or more of customer priority information and a transaction history. The second enterprise can determine if a third enterprise is authorized to access enterprise information of the first enterprise and/or the second enterprise.

Methods and apparatus for providing customer treatment information over a network

A method of administering a distributed priority queue structure that includes removing a highest priority item from a current root node of a tree structure to create a temporary root node, determining for each subtree connected to the temporary root node a subtree priority comprising the priority of the highest priority data item in the each subtree, determining as the highest priority subtree connected to the temporary root node the subtree connected to the temporary root node having the highest subtree priority, determining whether any of the one or more data items stored at the temporary root node has a higher priority than the highest subtree priority and directing an arrow to the subtree having the highest priority or to the temporary root itself if the priority of the data items stored at temporary root is higher than the priorities of the connected subtrees.

Distributed priority queue that maintains item locality

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for scheduling an event to automatically join a user to a conference call. In one aspect, the method includes receiving an invitation for a user to join a conference call, extracting from the invitation a scheduled conference call time, conference call address information, conference call authentication information, and a conference call modality, and scheduling an event to join the user to the conference call via the conference call modality at the scheduled conference call time based on the conference call address information and the conference call authentication information. In another aspect, the system retrieves a scheduled event at a scheduled time, extracts the address, authentication, and modality information for the conference, and joins the user to the conference automatically at the scheduled time.

Growing community of inventors

Dayton, NJ, United States of America

Krishna Kishore Dhara