Abstract: The invention describes Thinking Search Engines, a novel search technology that uses the data representation, problem solving and learning from experience techniques of Thinking Machines of U.S. patent application Ser. No. 11/204,346 by the author. Thinking Search Engines process documents and obtain their subjects in terms of the entities, templates, problems, concerns, solutions, and protocols that they describe whether or not these subjects are explicitly mentioned. They provide an initial ranking of search results by estimating the relative amount of information that each document contains for each of its subjects. During a search session, the machine records various data such as the address of the client machine, the files requested for each search query, the sequence, the elapsed time prior to each request, and the type of action that follows a request in the Session Information Table. Whenever a search session expires, its data is processed to populate the Experience Table of the Thinking Database.

Abstract: The invention describes Thinking Machines that learn from experience and apply their knowledge to search, discover, generalize and implement complete solutions to common problems. The machine represents a population of entities as Template, a set of properties and value ranges along with a time stamp indicating the time of the last occurrence, a frequency indicating the number of times its has been encountered, and a rating that decreases when it is involved in a problem and increases when it contributes to a solution. The templates provide a framework for identifying entities based on their properties and values. The templates are stored in a Thinking Database specifically designed to support the learning, thinking and problem resolution processes. The templates are updated as more entities are encountered, and evolve to reflect the knowledge that the system has about its environment. The system searches for solutions to a new problem using a novel technique called Scheduling Algorithm.