Abstract: Embodiments provide for dialog based speech recognition by clustering a plurality of nodes comprising a dialog tree into at least a first cluster and a second cluster; creating a first dataset of natural language sentences for the first cluster and a second dataset of natural language sentences for the second cluster; generating a first specialized language model (LM) associated with the first cluster based on the first dataset; and generating a second specialized LM associated with the second cluster based on the second dataset, wherein the first specialized LM is different from the second specialized LM.

Abstract: Embodiments provide for dialog based speech recognition by clustering a plurality of nodes comprising a dialog tree into at least a first cluster and a second cluster; creating a first dataset of natural language sentences for the first cluster and a second dataset of natural language sentences for the second cluster; generating a first specialized language model (LM) associated with the first cluster based on the first dataset; and generating a second specialized LM associated with the second cluster based on the second dataset, wherein the first specialized LM is different from the second specialized LM.

Abstract: Identifying life events within social network feeds. The method may include receiving social media data. The method may include identifying life event data within the social media data. The method may include determining a life event probability score associated with a life event class for the life event data using metadata. The method may include assigning a first life event class to each item of life event data based on the life event probability score. The method may include creating conversations by grouping the life event data. The method may include extracting metadata. The method may include determining a conversation probability score for each conversation based on the metadata and the life event probability score associated with each item of life event data. The method may include assigning a second life event class based on the conversation probability score. The method may include displaying the conversations based on user preferences.

Abstract: Identifying life events within social network feeds. The method may include receiving social media data. The method may include identifying life event data within the social media data. The method may include determining a life event probability score associated with a life event class for the life event data using metadata. The method may include assigning a first life event class to each item of life event data based on the life event probability score. The method may include creating conversations by grouping the life event data. The method may include extracting metadata. The method may include determining a conversation probability score for each conversation based on the metadata and the life event probability score associated with each item of life event data. The method may include assigning a second life event class based on the conversation probability score. The method may include displaying the conversations based on user preferences.

Abstract: The present disclosure relates generally to the field of segmenting social media users (such as users of a social media network) by means of life event detection (such as based upon social media messages and/or postings) and entity matching. In various embodiments, systems, methods and computer program products are provided.

Abstract: Backup and restore of digital data may utilize online social network parameters of a user to determine a number of parts into which to divide digital data and distribute the parts. A list of friends from the social network friends may be selected, e.g., based on a relationship to the user in the social network, to store the parts. The parts may be stored in a friend's device memory, each of the parts stored with a different friend. The digital data may be reconstructed by obtaining a threshold number of parts from the friends.

Abstract: Backup and restore of digital data may utilize online social network parameters of a user to determine a number of parts into which to divide digital data and distribute the parts. A list of friends from the social network friends may be selected, e.g., based on a relationship to the user in the social network, to store the parts. The parts may be stored in a friend's device memory, each of the parts stored with a different friend. The digital data may be reconstructed by obtaining a threshold number of parts from the friends.

Abstract: A shared data storage network, such as a peer-to-peer network, is managed according to individual member trust level. Members of the storage network make their local storage available to other members of the network. Members receive a storage-location recommendation based on (i) the type of data to be stored, and (ii) an individual trust level assigned to members providing storage resources in the network.

Abstract: The present disclosure relates generally to the field of segmenting social media users (such as users of a social media network) by means of life event detection (such as based upon social media messages and/or postings) and entity matching. In various embodiments, systems, methods and computer program products are provided.

Abstract: Identifying life events within social network feeds. The method may include receiving social media data. The method may include identifying life event data within the social media data. The method may include determining a life event probability score associated with a life event class for the life event data using metadata. The method may include assigning a first life event class to each item of life event data based on the life event probability score. The method may include creating conversations by grouping the life event data. The method may include extracting metadata. The method may include determining a conversation probability score for each conversation based on the metadata and the life event probability score associated with each item of life event data. The method may include assigning a second life event class based on the conversation probability score. The method may include displaying the conversations based on user preferences.

Abstract: A work process may be implemented based on social and enterprise networks. Candidate workers involved in the work process may be identified. A work-social network may be generated by merging social network information and work network information associated with the candidate workers. An overlap between the work-social network and the work process may be maximized or minimized by ranking the nodes representing the candidate workers in the work-social network. A set of top ranked nodes may be output as a list of selected workers to perform the work process.

Abstract: A work process may be implemented based on social and enterprise networks. Candidate workers involved in the work process may be identified. A work-social network may be generated by merging social network information and work network information associated with the candidate workers. An overlap between the work-social network and the work process may be maximized or minimized by ranking the nodes representing the candidate workers in the work-social network. A set of top ranked nodes may be output as a list of selected workers to perform the work process.

Abstract: Backup and restore of digital data may utilize online social network parameters of a user to determine a number of parts into which to divide digital data and distribute the parts. A list of friends from the social network friends may be selected, e.g., based on a relationship to the user in the social network, to store the parts. The parts may be stored in a friend's device memory, each of the parts stored with a different friend. The digital data may be reconstructed by obtaining a threshold number of parts from the friends.

Abstract: Backup and restore of digital data may utilize online social network parameters of a user to determine a number of parts into which to divide digital data and distribute the parts. A list of friends from the social network friends may be selected, e.g., based on a relationship to the user in the social network, to store the parts. The parts may be stored in a friend's device memory, each of the parts stored with a different friend. The digital data may be reconstructed by obtaining a threshold number of parts from the friends.

Abstract: A shared data storage network, such as a peer-to-peer network, is managed according to individual member trust level. Members of the storage network make their local storage available to other members of the network. Members receive a storage-location recommendation based on (i) the type of data to be stored, and (ii) an individual trust level assigned to members providing storage resources in the network.

Abstract: Techniques are provided for providing physical routes to target locations. The techniques include obtaining at least one target location from at least one user; determining at least one physical route to said at least one target location; and displaying said at least one determined physical route through a sequence of at least one sign display, wherein each sign display are configured to display a plurality of physical routes.

Abstract: An apparatus and a method is provided for verifying the setup of a current computer in need of repair, parsing and updating a previously created activity log file to provide usable steps that refer to the appropriate configuration settings for the computer being repaired. The method includes obtaining an indication of a problem on a remote computer, reviewing stored log files to determine if an old log file associated with the problem exists and if the old log file does not exist, creating a new log file to store steps associated with repair operations. The method also includes if the old log file exists, retrieving the old log file and obtaining the remote computer configurations, parsing the old log file to identify references to configuration settings and comparing the configuration settings in the old log file with the remote computer configuration.

Abstract: An apparatus and a method is provided for verifying the setup of a current computer in need of repair, parsing and updating a previously created activity log file to provide usable steps that refer to the appropriate configuration settings for the computer being repaired. The method includes obtaining an indication of a problem on a remote computer, reviewing stored log files to determine if an old log file associated with the problem exists and if the old log file does not exist, creating a new log file to store steps associated with repair operations. The method also includes if the old log file exists, retrieving the old log file and obtaining the remote computer configurations, parsing the old log file to identify references to configuration settings and comparing the configuration settings in the old log file with the remote computer configuration.

Abstract: A method for alerting a user of an incoming communication includes steps of: detecting a presence of the user; receiving, from at least one of a plurality of mobile devices of the user, information associated with the incoming communication; and alerting the user of the incoming communication.

Abstract: A method, information processing system and computer readable medium for emulating a mobile device on a computer is disclosed. The method includes storing an emulator program on the computer, wherein the emulator program imitates the functions and display of the mobile device. The method further includes establishing a connection between the mobile device and the computer and executing the emulator program on the computer, wherein an interface of the computer serves to interface with the emulator program. The method further includes synchronizing the emulator program and the mobile device such that the emulator program imitates in real time the functions and display of the mobile device. The method further allows the user to control and interact with the mobile devices from a centralized console on another device, such as a personal computer.