Abstract: In a document enrichment system, device buttons can be programmed to associate a number of personalities to the buttons on the device. These associations may be stored locally on the device. When the device with the programmed personality is activated on the device, the document produced is sent to a document enrichment system. Once enriched the document enrichment system notifies the user of the availability of the document in its new form.

Abstract: A system provides a plurality of controls for enriching the content of a meta-document. A meta-document includes document content and personalities that describe enrichment themes. The system is adapted to automatically, with user settable constrains, determine whether to propagate enrichment between documents using an interaction history. In addition, the system is adapted to automatically determine, with user settable constraints, the form that markup is to take in the document content.

Abstract: A text categorizer classifies a text object into one or more classes. The text categorizer includes a pre-processing module, a knowledge base, and an approximate reasoning module. The pre-processing module performs feature extraction, feature reduction, and fuzzy set generation to represent an unlabelled text object in terms of one or more fuzzy sets. The approximate reasoning module uses a measured degree of match between the one or more fuzzy set and categories represented by fuzzy rules in the knowledge base to assign labels of those categories that satisfy a selected decision making rule.

Abstract: An information space is created using a document. Entities from the document and its information space are used to create a database of entities. An auto-completion system uses contextual information surrounding a fragment from the document to formulate a query. The query is used to identify a set of entities in the database of entities that complete the fragment. An auto-correction system uses contextual information from identified errors in the document to formulate a query. The query is used to identify a set of entities in the database of entities that correct the error.

Abstract: A personality that identifies enrichment themes of a document is associated with a reading or mobile computing device. In one embodiment, a personality is associated with a document reference reading device and attached to each document reference recorded by the document reference reading device. The personality and each recorded document reference are transmitted to a meta-document server. The meta-document server enriches document content identified by the document reference in accordance with the associated personality. The enriched document content is then made available to the user of the reading device.

Abstract: A technique for representing an information need and employing one or more filters to select documents that satisfy the represented information need, including a technique of creating filters that involves (a) dividing a set of documents into one or more subsets such that each subset can be used as the source of features for creating a filtering profile or used to set or validate the score threshold for the profile and (b) determining whether multiple profiles are required and how to combine them to create an effective filter. Multiple profiles can be incorporated into an individual filter and the individual filters combined to create an ensemble filter. Ensemble filters can then be further combined to create meta filters.

Abstract: A system generates a query using an entity extractor, a categorizer, a query generator, and a short run aspect vector. The entity extractor identifies a set of entities in selected document content for searching information related thereto using an information retrieval system. The categorizer defines an organized classification of document content with each class in the organization of content having associated therewith a classification label that corresponds to a category of information in the information retrieval system. The categorizer assigns the selected document content a classification label from the organized classification of content. A query generator formulates a query that restricts a search at the information retrieval system to the category of information in the information retrieval system identified by the assigned classification label.

Abstract: A technique for representing an information need and employing one or more filters to select documents that satisfy the represented information need, including a technique of creating filters that involves (a) dividing a set of documents into one or more subsets such that each subset can be used as the source of features for creating a filtering profile or used to set or validate the score threshold for the profile and (b) determining whether multiple profiles are required and how to combine them to create an effective filter. Multiple profiles can be incorporated into an individual filter and the individual filters combined to create an ensemble filter. Ensemble filters can then be further combined to create meta filters.

Abstract: A system operates using meta-documents which include document content associated with one or more personalities. Each personality is associated with a set of document service requests. Users are provided different techniques for creating personalities and modifying existing personalities. These techniques include: the use of an algebra to tailor existing personalities, the use of a list of links or documents to create a personality, the use of predefined personalities and knowledge levels in a field to create new personalities, the use of question answering techniques, and the use of learning personalities. Specified personalities are then used to enrich document content by integrating into corresponding meta-documents the results received from their document service requests.

Abstract: A text categorizer classifies a text object into one or more classes. The text categorizer includes a pre-processing module, a knowledge base, and an approximate reasoning module. The pre-processing module performs feature extraction, feature reduction, and fuzzy set generation to represent an unlabelled text object in terms of one or more fuzzy sets. The approximate reasoning module uses a measured degree of match between the one or more fuzzy set and categories represented by fuzzy rules in the knowledge base to assign labels of those categories that satisfy a selected decision making rule.

Abstract: A system generates a query using an entity extractor, a categorizer, a query generator, and a short run aspect vector. The entity extractor identifies a set of entities in selected document content for searching information related thereto using an information retrieval system. The categorizer defines an organized classification of document content with each class in the organization of content having associated therewith a classification label that corresponds to a category of information in the information retrieval system. The categorizer assigns the selected document content a classification label from the organized classification of content. A query generator formulates a query that restricts a search at the information retrieval system to the category of information in the information retrieval system identified by the assigned classification label.

Abstract: A system provides a plurality of controls for enriching the content of a meta-document. A meta-document includes document content and personalities that describe enrichment themes. The system is adapted to automatically, with user settable constrains, determine whether to propagate enrichment between documents using an interaction history. In addition, the system is adapted to automatically determine, with user settable constraints, the form that markup is to take in the document content.

Abstract: A system operates using meta-documents which include document content associated with one or more personalities. Each personality is associated with a set of document service requests. Users are provided different techniques for creating personalities and modifying existing personalities. These techniques include: the use of an algebra to tailor existing personalities, the use of a list of links or documents to create a personality, the use of predefined personalities and knowledge levels in a field to create new personalities, the use of question answering techniques, and the use of learning personalities. Specified personalities are then used to enrich document content by integrating into corresponding meta-documents the results received from their document service requests.

Abstract: An information space is created using a document. Entities from the document and its information space are used to create a database of entities. An auto-completion system uses contextual information surrounding a fragment from the document to formulate a query. The query is used to identify a set of entities in the database of entities that complete the fragment. An auto-correction system uses contextual information from identified errors in the document to formulate a query. The query is used to identify a set of entities in the database of entities that correct the error.