Abstract: A system and method for communication and collaboration are disclosed. A generalized annotation based mechanism using an emergent self organization characteristic of the natural language of the annotations allows users to search for relevant items, users to search for relevant users, and items to search for relevant users based on aggregation of stored annotations having associations between keywords, items and users in a context space. Aggregations based on correlations between users, items and keywords, are used to form a collaborative content relevance that allows users to be directed to items or other users, and items to be directed to users.
Abstract: An organisation system (5) for organizing items (11), the system (5) comprising: a data structure (10) associating at least one semantic metadata (12) with an item (11) to define a directional relationship between a concept and the item (11); and a user interface (20) to express the at least one semantic metadata (12) in at least one natural language using a description or at least one keyword corresponding to the concept in the at least one natural language; wherein the at least one semantic metadata (12) corresponds to the concept that is a characteristic of the item (11); and the at least one semantic metadata (12) and the item (11) are referenced by unique machine-readable identifiers
Abstract: A system and method for communication and collaboration that uses a generalized annotation based mechanism such that items can be shared amongst users and both items and users can be searched and ranked based on existing Information Retrieval ranking techniques. A new method is introduced for clustering users and items simultaneously on the basis of category contexts. These mechanisms are leveraged to create a mechanism that allows for publishing and subscribing items based on context.
Abstract: Disclosed is a semantic user interface system that allows text information to be tagged with machine-readable IDs that are associated with concepts for conveying information without any ambiguity or without being hampered by the limitations of human languages. Typically, a plurality of vocabularies are stored across a network, and each vocabulary includes a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID. An input interface accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description. The machine-readable IDs can carry information in the form of concepts without any ambiguity as opposed to text information.