Abstract: The present invention provides search engine methods and systems for generating highly personalized and relevant search results based on the context of a user's search constraint and user characteristics. In an embodiment, upon receipt of a user's search constraint, the method determines all semantic variations for each word within the user search constraint. Additionally, topics can be determined within the user constraint. For each unique word and topic within the user search constraint, possible contexts are determined. A matrix of feasible context scenarios is established. Each context scenario is ranked to determine the most likely context scenario for which the user search constraint relates based on user characteristics. In one embodiment, the weighting used to rank the contexts is based on previous user searches and/or knowledge of their interests. Search results associated with the highest ranking context are provided to the user, along with topics associated with lower ranked contexts.

Abstract: The present invention provides systems and methods for decision making support. The decision making support can be used, for example, for help desk troubleshooting, medical diagnosis, financial planning, and expert device. The decision support system of the invention includes a processor and a memory having a decision support program module, a phase dictionary, one or more solution nodes and optionally a topic identification information module. The decision support module is configured to enable the processor to receive a problem constraint and one or more user-specified phrases, which are then used to search nodes in a solution domain to identify a set of nodes potentially related to the user's problem or question. The set of nodes potentially related to the user's problem or question are ranked and displayed. Methods to determine potential solution nodes and to update solution nodes within the decision support system are provided.

Abstract: The present invention provides systems and methods for decision making support. The decision making support can be used, for example, for help desk troubleshooting, medical diagnosis, financial planning, and expert device. The decision support system of the invention includes a processor and a memory having a decision support program module, a phase dictionary, one or more solution nodes and optionally a topic identification information module. The decision support module is configured to enable the processor to receive a problem constraint and one or more user-specified phrases, which are then used to search nodes in a solution domain to identify a set of nodes potentially related to the user's problem or question. The set of nodes potentially related to the user's problem or question are ranked and displayed. Methods to determine potential solution nodes and to update solution nodes within the decision support system are provided.

Abstract: A technique to determine topics associated with, or classifications for, a data corpus uses an initial domain-specific word list to identify word combinations (one or more words) that appear in the data corpus significantly more often than expected. Word combinations so identified are selected as topics and associated with a user-specified level of granularity. For example, topics may be associated with each table entry, each image, each sentence, each paragraph, or an entire file. Topics may be used to guide information retrieval and/or the display of topic classifications during user query operations.