Abstract: There is disclosed a system and method for processing multi-modal collaboration. In an embodiment communication received from multiple modes are converted into a common format. Using various conversion modules, the communication may be converted into a common electronic text format (e.g. ASCII text) that contains keywords. Once the communication is converted into a common format, the information contained in the communication may be analyzed and consolidated into related areas or topics. The consolidated information may then be searched for common references in order to augment the information context.

Abstract: There is disclosed a method of facilitating interaction between users of an electronic community. In an embodiment, the method comprises: reviewing a user activity log for each user in the electronic community; executing a natural language parser to extract significant noun phrases from the user activity log; updating user profiles from the newly extracted noun phrases, based on their usage frequency and importance value; and storing the updated profiles in a user profile and relationship data base; and executing a similarity based clustering algorithm to cluster user profiles, thereby discovering relationships among users and storing them in a user profile and relationship database. The method may further comprise displaying for each user the one or more relationships to which the user is assigned, together with a list of users assigned to the one or more relationships.

Abstract: A method and an associated computer program product, computing system, and process for supporting computer infrastructure for prompting an end user with a preferred sequence of commands which performs an activity in a least number of inputs. The method begins by monitoring a computer system for both input received from the end user and state transitions as a result of the computer receiving the end user input. The input received facilitates an activity the end user whishes to execute; the state transitions being the result of executing the activity. Next, defining the input received from the end user in a meaningful way. Then comparing the input received with at least one other command sequences that accomplish the same activity as the end user's input. Finally, prompting the end user with a preferred sequence of commands which performs the activity with the least number of inputs possible.

Abstract: A system for clustering data objects includes a module for calculating an importance value of at least one member in a first data object represented as a variable length vector of 0 to N members and a clustering module for dynamically forming a plurality of clusters containing one or more data objects. The clustering module is configured to associate the first data object with at least one of the plurality of clusters in dependence upon the at least one member's similarity value in comparison to members in other data objects. The clustering module may be configured to cluster the first data object into a plurality of clusters if it has at least two members and each member belongs to a different cluster.

Abstract: A method for prompting an end user with a preferred sequence of commands which performs an activity in a least number of inputs. The method begins by monitoring a computer system for both input received from the end user and state transitions as a result of the computer receiving the end user input. The input received facilitates an activity the end user whishes to execute; the state transitions being the result of executing the activity. Next, defining the input received from the end user in a meaningful way. Then comparing the input received with at least one other command sequences that accomplish the same activity as the end user's input. Finally, prompting the end user with a preferred sequence of commands which performs the activity with the least number of inputs possible.

Abstract: There is disclosed a method of facilitating interaction between users of an electronic community. In an embodiment, the method comprises: reviewing a user activity log for each user in the electronic community; executing a natural language parser to extract significant noun phrases from the user activity log; updating user profiles from the newly extracted noun phrases, based on their usage frequency and importance value; and storing the updated profiles in a user profile and relationship data base; and executing a similarity based clustering algorithm to cluster user profiles, thereby discovering relationships among users and storing them in a user profile and relationship database. The method may further comprise displaying for each user the one or more relationships to which the user is assigned, together with a list of users assigned to the one or more relationships.

Abstract: There is disclosed a system and method for processing multi-modal collaboration. In an embodiment communication received from multiple modes are converted into a common format. Using various conversion modules, the communication may be converted into a common electronic text format (e.g. ASCII text) that contains keywords. Once the communication is converted into a common format, the information contained in the communication may be analyzed and consolidated into related areas or topics. The consolidated information may then be searched for common references in order to augment the information context.

Abstract: A system for clustering data objects includes a module for calculating an importance value of at least one member in a first data object represented as a variable length vector of 0 to N members and a clustering module for dynamically forming a plurality of clusters containing one or more data objects. The clustering module is configured to associate the first data object with at least one of the plurality of clusters in dependence upon the at least one member's similarity value in comparison to members in other data objects. The clustering module may be configured to cluster the first data object into a plurality of clusters if it has at least two members and each member belongs to a different cluster.