Abstract: Novel tools and techniques for determining suitability and/or desirability of a prospective residence for a user. In some embodiments, a computer might receive a list of real estate listings, each pertaining to, and including a plurality of attributes about, an available home. The computer might collect information about factors relating to a user, generate a user profile based at least in part on the factors, and infer a prioritized list of real estate listing characteristics to satisfy the user based on a prioritized list of user criteria. The computer might subsequently generate and prioritize a list of potential homes from the list of real estate listings, based on comparisons, and at least in part on matches, between the prioritized list of real estate listing characteristics and attributes of at least some potential homes in the listings. The computer might subsequently display the prioritized list of potential homes to the user.

Abstract: A real-time interactive document summarization system which allows the user to continuously control the amount of detail to be included in a document summary.

Abstract: A real-time interactive document summarization system which allows the user to continuously control the amount of detail to be included in a document summary.

Abstract: A computer system user interface provides a document summary which allows the user to more easily identify the contents and subject matter of the document.

Abstract: A computer system user interface provides a document summary which allows the user to more easily identify the contents and subject matter of the document.

Abstract: Information presented to a user via an information access system is ranked according to a prediction of the likely degree of relevance to the user's interests. A profile of interests is stored for each user having access to the system. Items of information to be presented to a user are ranked according to their likely degree of relevance to that user and displayed in order of ranking. The prediction of relevance is carried out by combining data pertaining to the content of each item of information with other data regarding correlations of interests between users. A value indicative of the content of a document can be added to another value which defines user correlation, to produce a ranking score for a document. Alternatively, multiple regression analysis or evolutionary programming can be carried out with respect to various factors pertaining to document content and user correlation, to generate a prediction of relevance.

Abstract: A real-time interactive document summarization system which allows the user to continuously control the amount of detail to be included in a document summary.

Abstract: A computer system user interface provides a document summary which allows the user to more easily identify the contents and subject matter of the document.

Abstract: An information access system stores items of information in an unstructured global database. When a user requests access to the system, the system delivers to that user an identification of only those items of information which are believed to be relevant to the user's interest. The determination as to the items of information that are relevant to a user is carried out by ranking each available item in accordance with any one or more techniques. In one approach, the content of each document is matched with an adaptive profile of a user's interest. In another approach, a feedback mechanism is provided to allow users to indicate their degree of interest in each item of information. These indications are used to determine whether other users, who have similar or dissimilar interests, will find a particular item to be relevant.

Abstract: Information presented to a user via an information access system is ranked according to a prediction of the likely degree of relevance to the user's interests. A profile of interests is stored for each user having access to the system. Items of information to be presented to a user are ranked according to their likely degree of relevance to that user and displayed in order of ranking. The prediction of relevance is carried out by combining data pertaining to the content of each item of information with other data regarding correlations of interests between users. A value indicative of the content of a document can be added to another value which defines user correlation, to produce a ranking score for a document. Alternatively, multiple regression analysis or evolutionary programming can be carried out with respect to various factors pertaining to document content and user correlation, to generate a prediction of relevance.