Abstract: Systems and methods for attacks, countermeasures, archiving, data leak prevention, and other novel services relating to active messages are disclosed. Among other things, a system can replace active content with static content in a message, can replace static content with active content in a message, and can use active messaging to provide enhanced on-hold message functions.

Abstract: Methods of retrieving documents using a language model are disclosed. A method may include preparing a language model of a plurality of documents, receiving a query, processing the query using the language model, and using the processed query to retrieve documents responding to the query via the search engine. The methods may be implemented in software and/or hardware on computing devices, including personal computers, telephones, servers, and others.

Abstract: Techniques for grouping related objects such as documents and files using quantum clustering are disclosed. A method may include constructing a feature-object database of multiple objects. The feature-object database may have quantized selected features as keys. A connected objects database maybe built. Clusters of connected objects may be identified in the connected objects database. The clusters of identified objects may be evaluated to determine groups of related objects. The method may be implemented on a computing device.

Abstract: Techniques for grouping related objects such as documents and files using quantum clustering are disclosed. A method may include constructing a feature-object database of multiple objects. The feature-object database may have quantized selected features as keys. A connected objects database maybe built. Clusters of connected objects may be identified in the connected objects database. The clusters of identified objects may be evaluated to determine groups of related objects. The method may be implemented on a computing device.

Abstract: Techniques for grouping related objects such as documents and files using quantum clustering are disclosed. A method may include constructing a feature-object database of multiple objects. The feature-object database may have quantized selected features as keys. A connected objects database maybe built. Clusters of connected objects may be identified in the connected objects database. The clusters of identified objects may be evaluated to determine groups of related objects. The method may be implemented on a computing device.

Abstract: Techniques for grouping related objects such as documents and files using quantum clustering are disclosed. A method may include constructing a feature-object database of multiple objects. The feature-object database may have quantized selected features as keys. A connected objects database maybe built. Clusters of connected objects may be identified in the connected objects database. The clusters of identified objects may be evaluated to determine groups of related objects. The method may be implemented on a computing device.

Abstract: Methods of retrieving documents using a language model are disclosed. A method may include preparing a language model of a plurality of documents, receiving a query, processing the query using the language model, and using the processed query to retrieve documents responding to the query via the search engine. The methods may be implemented in software and/or hardware on computing devices, including personal computers, telephones, servers, and others.

Abstract: A process and system for database storage and retrieval are described along with methods for obtaining semantic profiles from a training text corpus, i.e., text of known relevance, a method for using the training to guide context-relevant document retrieval, and a method for limiting the range of documents that need to be searched after a query. A neural network is used to extract semantic profiles from text corpus. A new set of documents, such as world wide web pages obtained from the Internet, is then submitted for processing to the same neural network, which computes a semantic profile representation for these pages using the semantic relations learned from profiling the training documents. These semantic profiles are then organized into clusters in order to minimize the time required to answer a query. When a user queries the database, i.e., the set of documents, his or her query is similarly transformed into a semantic profile and compared with the semantic profiles of each cluster of documents.