International Business Machines Corporation

Yu Zhang

Peter Currie Boyle

Currie Peter Boyle

In a system, a similarity based clustering algorithm is executed to generate clusters of user profiles. Each cluster includes a group of users in an electronic community. Each cluster represents a relationship between the users in each group that each cluster includes. Each cluster is stored in a user profile and relationship database. The similarity based clustering algorithm includes s a member importance function and a member similarity function. The member importance function ascertains an importance value of keywords as a depth of the keywords in a semantic hierarchical tree. The member similarity function ascertains a similarity distance between keywords as a path distance between the keywords in the semantic hierarchical tree. Executing the similarity based clustering algorithm includes: using the member importance function and the member similarity function to ascertain the clusters.

Expanding network relationships

A method and system for processing user profiles of a plurality of users in an electronic community. Noun phrases are extracted from activities of each user logged in an activity log server, each user having an existing user profile stored in a user profile and relationship database that is external to the activity log server. The existing user profiles in the user profile and relationship database are updated from the extracted noun phrases, a keyword being associated with each determined noun phrase and being within a semantic hierarchical tree, the updating based on a usage frequency of the extracted noun phrases and an importance value of the keywords.

Processing user profiles of users in an electronic community

A method of integrated automatic support and assistance includes identifying a user and retrieving models representing the user's device, apparatus, service, or system, receiving a query from the user, as necessary refining the query, determining if the received query is a machine translatable query, restructuring machine translatable terms of the received query into semantic components based upon the retrieved models, determining a set of candidate knowledge bases both related to the semantic components, submitting the machine translatable query to each knowledge base of the set of candidate knowledge bases, receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting, formatting the set of responses, submitting the formatted set of responses to the user, determining if a response of the submitted formatted set of responses is accepted by the user, applying updated weights within the formatted set of responses, and storing the updated weights for future queries.

Integrated automatic user support and assistance

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.

System and method for processing multi-modal communication within a workgroup

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. The method may also comprise storing for each user the relationship to which the user is assigned in a user profile and relationship database.

System and method for interaction between users of an online community

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.

Prompting of an end user with commands

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.

Clustering data objects

There is disclosed a system and method for interpreting and describing graphic images. In an embodiment, the method of inserting a description of an image into an audio recording includes: interpreting an image and producing a word description of the image including at least one image keyword; parsing an audio recording into a plurality of audio clips, and producing a transcription of each audio clip, each audio clip transcription including at least one audio keyword; calculating a similarity distance between the at least one image keyword and the at least one audio keyword of each audio clip; and selecting the audio clip transcription having a shortest similarity distance to the at least one image keyword as a location to insert the word description of the image. The word description of the image can then be appended to the selected audio clip to produce an augmented audio recording including the interpreted word description of the image.

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Vancouver, Canada

Yu Zhang