Abstract: A service based automated assistant uses a response logic to connect a user to helpful responses. The response logic involves a bidding system that uses contract net initiators that generate and evaluate bids and contract net responders that transmit the bids and bid evaluations downstream in the logic to service agents for evaluation and bidding, and upstream back to the user.

Abstract: A system and a method for organizing optimal paths in a sensor network. Optimal paths are determined based on an objective function that balances the performance and energy consumption of sensor nodes. Each sensor node stores and updates pheromone values and aging factors associated with each of its neighbor nodes. The pheromone values provide an indication of the speed of a given path, while the aging factor represents the use. Paths are compared using these variables and an optimal path is selected on each transfer so that the load is spread across a variety of sensor nodes, increasing network life.

Abstract: Mixed mode inferencing is provided by creating an extension to a RETE network to handle both forward and backward chaining efficiently. The extended RETE network is traversed from a root node through intermediate nodes to the rules of the network. The intermediate nodes contain objects that have values assigned by rules, and the intermediate nodes are linked to those rules appropriately. When using the network in a backward chaining context, rules linked to the intermediate node of interest are checked to see if they are active and the rule is solvable. If not, the related rules are checked. Because the system takes advantage of the previously formed RETE network, these checks can be done at the rule nodes without the need to retest each condition.

Abstract: Mixed mode inferencing is provided by creating an extension to a RETE network to handle both forward and backward chaining efficiently. The extended RETE network is traversed from a root node through intermediate nodes to the rules of the network. The intermediate nodes contain objects that have values assigned by rules, and the intermediate nodes are linked to those rules appropriately. When using the network in a backward chaining context, rules linked to the intermediate node of interest are checked to see if they are active and the rule is solvable. If not, the related rules are checked. Because the system takes advantage of the previously formed RETE network, these checks can be done at the rule nodes without the need to retest each condition.

Abstract: An intelligent information-mining system extracts desired intelligent information from unstructured text data in documents to categorize the unstructured text data based on the extracted desired intelligent information. This is accomplished by obtaining unstructured text data from documents in an electronic format. The obtained unstructured text data is then transformed into unstructured neutral format data. The transformed unstructured neutral format data is then converted into structured data based on desired intelligent information. Desired intelligent information is then extracted from the structured data by using a multilayer self-organizing maps (MSOM) algorithm.

Abstract: A system and a method for an automated intelligent information mining includes receiving unstructured text from various text sources; extracting multiple key-phrases from the unstructured text; generating template and dynamic information contextual relation maps by mapping the extracted key-phrases to three-dimensional maps using a self organizing map, and a gaussian distribution technique. Further, the technique includes forming word clusters and constructing corresponding key-phrase frequency histograms for each of the generated contextual relation maps. Template and dynamic information three-dimensional structured document maps from the constructed phrase frequency histograms and the generated self-organizing maps. Desired information is extracted by mapping the generated dynamic information three-dimensional structured map onto the template three-dimensional structured map. A fuzzy prediction algorithm is used in possible error correction in extracting the desired intelligent information.

Abstract: A system and a method for organizing optimal paths in a sensor network. Optimal paths are determined based on an objective function that balances the performance and energy consumption of sensor nodes. Each sensor node stores and updates pheromone values and aging factors associated with each of its neighbor nodes. The pheromone values provide an indication of the speed of a given path, while the aging factor represents the use. Paths are compared using these variables and an optimal path is selected on each transfer so that the load is spread across a variety of sensor nodes, increasing network life.

Abstract: An automated customer support tool. A web server receives one or more queries regarding the product from a customer. A categorizer coupled to the web server categorizes the received queries based on a type of query, to determine whether the answers to the queries can be automatically communicated to the customer. An FAQ extractor extracts one or more corresponding product FAQs from respective product FAQ data bases. A key-word extractor extracts one or more key-words from the received queries and the extracted product FAQs. The key-word extractor further transforms the extracted key words to unique numerical representations. An analyzer coupled to the key-word extractor represents the transformed key-words into respective query and product FAQ vector forms. The analyzer further applies a convolution algorithm to each of the query vector forms, with each of the product FAQ vector forms separately and obtains one or more appropriate answers to the queries.

Abstract: A system and a method for an automated intelligent information mining includes receiving unstructured text from various text sources; extracting multiple key-phrases from the unstructured text; generating template and dynamic information contextual relation maps by mapping the extracted key-phrases to three-dimensional maps using a self organizing map, and a gaussian distribution technique. Further, the technique includes forming word clusters and constructing corresponding key-phrase frequency histograms for each of the generated contextual relation maps. Template and dynamic information three-dimensional structured document maps from the constructed phrase frequency histograms and the generated self-organizing maps. Desired information is extracted by mapping the generated dynamic information three-dimensional structured map onto the template three-dimensional structured map. A fuzzy prediction algorithm is used in possible error correction in extracting the desired intelligent information.

Abstract: The present invention provides an intelligent information-mining system to extract desired intelligent information from unstructured text data in documents to categorize the unstructured text data based on the extracted desired intelligent information. This is accomplished by obtaining unstructured text data from documents in an electronic format. The obtained unstructured text data is then transformed into unstructured neutral format data. The transformed unstructured neutral format data is then converted into structured data based on desired intelligent information. Desired intelligent information is then extracted from the structured data by using a multilayer self-organizing maps (MSOM) algorithm.

Abstract: An automated customer support tool. A web server receives one or more queries regarding the product from a customer. A categorizer coupled to the web server categorizes the received queries based on a type of query, to determine whether the answers to the queries can be automatically communicated to the customer. An FAQ extractor extracts one or more corresponding product FAQs from respective product FAQ data bases. A key-word extractor extracts one or more key-words from the received queries and the extracted product FAQs. The key-word extractor further transforms the extracted key words to unique numerical representations. An analyzer coupled to the key-word extractor represents the transformed key-words into respective query and product FAQ vector forms. The analyzer further applies a convolution algorithm to each of the query vector forms, with each of the product FAQ vector forms separately and obtains one or more appropriate answers to the queries.