Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A computing system has a user interface allowing a user to view and input data related to concepts in a knowledge area associated with the user, an observation sub-system to centralize data and to identify a plurality of knowledge concepts, a conceptualization sub-system to generate a plurality of nodes within an ontological mapping, wherein each of the nodes corresponds to a certain one of the plurality of identified knowledge concepts identified by the observation sub-system, a relationship identification sub-system to create relationships between at least some of the plurality of identified knowledge concepts, and attribute affinity weights to the relationships, a change refinement sub-system to modify at least one of the plurality of nodes, affinity weights and relationships based upon information associated with the user, and a non-transitory knowledge store to store the information associated with the user pertaining to a sub-plurality of the plurality of identified knowledge concepts.

Abstract: A system may include multiple personal data sources and a machine-implemented data extractor and correlator configured to retrieve personal data from at least one of the personal data sources. The data extractor and correlator may extract information from unstructured data within the retrieved personal data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data. A natural language query module may be configured to receive a natural language query from a user and provide a response to the natural language query based at least in part on one or both of the previously stored structured data and the additional structured data.

Abstract: A computing system has a user interface allowing a user to view and input data related to concepts in a knowledge area associated with the user, an observation sub-system to centralize data and to identify a plurality of knowledge concepts, a conceptualization sub-system to generate a plurality of nodes within an ontological mapping, wherein each of the nodes corresponds to a certain one of the plurality of identified knowledge concepts identified by the observation sub-system, a relationship identification sub-system to create relationships between at least some of the plurality of identified knowledge concepts, and attribute affinity weights to the relationships, a change refinement sub-system to modify at least one of the plurality of nodes, affinity weights and relationships based upon information associated with the user, and a non-transitory knowledge store to store the information associated with the user pertaining to a sub-plurality of the plurality of identified knowledge concepts.

Abstract: Techniques for using instant messaging preferences and settings are used for predictive communications, including routing of data traffic, are provided. A voice call can be routed over a packet-based network if a voice network is not available, or for other reasons. In addition to voice calls, embodiments of the invention can route video calls, multimedia communications and other communications. In some implementations, an instant message presence can be queried for in determining how to route a voice-over-IP or PSTN telephone call. Thus, a call might be routed to a computer or computing device unrelated to the location of the PSTN telephone line being called, if an associated instant messenger presence is detected on that computer or computing device.

Abstract: A system, method, and apparatus are directed towards providing integrated access to call information to an end-user using any of a variety of client applications, including an Instant Messaging (IM), a web-browser, and/or a VOIP client. An end-user may employ any of the above client applications to establish a communication session and enable an integrated access display for use in managing such call information as audio messages, call histories, and instant messaging conversations. The integrated access display may be managed through an intelligent integration client that may reside on a client device, such as a personal computer, a mobile device, a VOIP phone, and the like. Through the intelligent integration client, the end-user may search, retrieve, and/or view the call information. For example, using the VOIP phone, the end-user may search for and access a stored audio message, such as a voice mail message, or the like.

Abstract: A system, method, and apparatus are directed towards a system, method, and apparatus for managing a communication session by dynamically selecting a CODEC. A client device requests a communication session with a receiver device. If available, historical information may be used to establish an initial CODEC and its associated sampling frequency for the communication session. Signals, such as a white noise signal, and/or a ring tone may be sent between the client device and the receiver to determine a metric for the communication session. The metric may be used to adjust the CODEC and/or its sampling frequency for the communication session. In one embodiment, if it is determined that the sampling frequency is less than a minimum determined value, a message may be sent to the client device advising that the current communication session be terminated.

Abstract: A system, method, and apparatus are directed towards managing an audio message, such as a Voice over Internet Protocol (VOIP) message over a network. The invention employs a statistical mechanism to automatically optimize a gain control for setting a volume of an audio message being sent by a client device. An initial gain value is automatically adjusted based, in part, on a statistical sampling of energy levels in the audio message. Environmental factors, such as a sound card within the client device, background noise, and the like, may also be considered through a setting of a servo coefficient that may be used to map between volume levels and decibel levels. The servo coefficient may also be adjusted based, at least in part, on decibel (dB) feedback information from a destination device for which the audio message is intended.

Abstract: An integrated VoIP unified message processing system includes a voice platform that processes data in native VoIP format. There is no use of hardware telephone interface cards (TICs) or software transcoding to transform data to PCM or other formats. Cost reductions are achieved by the elimination of expensive dedicated hardware and scalability is achieved by obviating the need for software transcoding.

Abstract: A system, method, and apparatus are directed towards managing a Voice over IP (VOIP) messages over a network, employing the Real-time Transport Protocol (RTP) and Session Initiation Protocol (SIP) over the Transmission Control Protocol (TCP). The VOIP messages are sent by a source device to a destination device through a relay server. The relay server may throttle the VOIP messages employing buffer management. When the buffer is substantially full, the relay server will drop packets from the source device. Indication of the lost packets may be provided to the source device through a Real-time Transport Control Protocol (RTCP) report. The source device may then employ the RTCP report to modify a type of codec employed, and thereby adjust a rate of flow of VOIP packets sent towards the destination device. Additionally, the relay server may provide port translation services for RTP/RTCP packets between the source and destination devices.

Abstract: Techniques for using billing services to manage a personal address book are provided. The techniques comprise receiving a call detail record (CDR) for a plain old telephone system (POTS) or a voice-over-IP (VOIP) call by a user. The CDR is created by a telecommunication carrier that routed the call. The CDR may be stored on a telecommunications server associated with the telecommunications carrier. Address information for the call is determined from the CDR. This address information is added to the personal address book for the user. This address information may be available for the user when using an IM client.

Abstract: A voice converter includes upstream and downstream resource managers for allocation half-duplex resources of a full duplex DSP transcoder. The resource managers schedule available upstream or downstream resources and provide transcoded voice data to requesting applications.

Abstract: A system, method, and apparatus are directed towards managing a Voice over IP (VOIP) message over a network, where the VOIP message may employ the Real-time Transport Protocol (RTP) and possibly Session Initiation Protocol (SIP) over the User Datagram Protocol (UDP). The invention enables a VOIP client device, such as an IP phone, and the like, to communicate a message to a local proxy residing on a local computing device. The communications between the VOIP device and the local proxy may employ SIP/RTP over UDP. Upon receipt of the communications, the local proxy converts the transport protocol to another transport protocol, such as Transmission Control Protocol (TCP). The local proxy may also perform a port translation on the message. The converted communications may then be sent to a remote server, where it may be employed in its present SIP/RTP over TCP format, or be converted back to using UDP.

Abstract: A system, method, and apparatus are directed towards routing a Voice over IP (VOIP) messages over a network. The VOIP messages are sent by a source client device to a destination client device through a portal service that has access to multiple routing services such as peering partners, carriers, etc. A VOIP system of the portal service aggregates call quality data after each VOIP call over each routing service. The call quality data is analyzed to determine a perception factor for each routing service at various times of day, days of the week, day of the year, geographic areas, and the like. When a VOIP call is requested through the portal service, the VOIP system determines a current cost, a current quality of service, and the perception factor for each routing service. A weighting is applied to each criterion and a routing service is selected for routing the VOIP call.