Abstract: In one aspect of the invention, a method of performing a conceptual similarity search comprises the steps of: generating one or more conceptual word-chains from one or more documents to be used in the conceptual similarity search; building a conceptual index of documents with the one or more word-chains; and evaluating a similarity query using the conceptual index. The evaluating step preferably returns one or more of the closest documents resulting from the search; one or more matching word-chains in the one or more documents; and one or more matching topical words of the one or more documents.

Abstract: Techniques are provided for incorporating human or user interaction in accordance with the design and/or performance of data mining applications such as similarity determination and classification. Such user-centered techniques permit the mining of interesting characteristics of data in a data or feature space. For example, such interesting characteristics that may be determined in accordance with the user-centered mining techniques of the invention may include a determination of similarity among different data objects, as well the determination of individual class labels. These techniques allow effective data mining applications to be performed in accordance with high dimensional data.

Abstract: Techniques are provided for incorporating human or user interaction in accordance with the design and/or performance of data mining applications such as similarity determination and classification. Such user-centered techniques permit the mining of interesting characteristics of data in a data or feature space. For example, such interesting characteristics that may be determined in accordance with the user-centered mining techniques of the invention may include a determination of similarity among different data objects, as well the determination of individual class labels. These techniques allow effective data mining applications to be performed in accordance with high dimensional data.

Abstract: A method for mining incomplete data sets that avoids the process of having to extrapolate the attributes, and instead concentrate on the use of conceptual representations in order to mine the data sets. The idea in using conceptual representations is that even though many attributes may be missing, it is possible to accurately guess the behavior of the data along certain pre-specified directions, i.e., the conceptual directions of the data set.

Abstract: A technique of the system for generating a reduced representation of input data, wherein the input data has a first set of feature variables and a class variable associated therewith, comprises the following steps. A second set of feature variables is determined from the first set of feature variables, wherein the second set of feature variables corresponds to mutually orthogonal vectors. Then, one or more of the feature variables associated with the second set of feature variables are selected based on a level of discrimination with respect to the class variable. The input data is then represented using the one or more selected feature variables.

Abstract: A method for providing product recommendations to customers in an e-commerce environment includes the step of generating content and compatibility representations of products corresponding to a plurality of customers. A similarity function is calculated between pairs of content attributes corresponding to the products. A similarity function is calculated between pairs of compatibility attributes corresponding to the products. The plurality of customers are clustered into a plurality of peer groups. For a given customer, a closest peer group of the plurality of peer groups is determined. At least one potential recommendation is then generated for the given customer based on the closest peer group.

Abstract: Techniques are provided for finding query responses from database queries using an interactive process between a user (e.g., a person entering a query to a database) and a computer system (e.g., a computing system upon which the database resides or which has access to the database). The interactive process comprises providing the user with one or more visual perspectives as feedback on the distribution of points in the database. These visual perspectives may be considered by the user in order for the user to provide feedback to the computer system. The computer system may then use the user-provided feedback to determine the best response to the query.

Abstract: A method for scheduling delivery of digital objects over a network, in accordance with the invention, includes the steps of providing a user interface for selecting objects to be transmitted thereto, selecting at least one object to be transmitted to the user interface, identifying and receiving in-progress object transmissions corresponding to the at least one selected object, identifying portions of the at least one object not yet received to request transmission of the portions of the at least one object not yet received and receiving remaining portions of the at least one object during additional in-progress transmissions. A system is also included.

Abstract: A system and method for developing association rules which are personalized for a customer. The method includes partitioning (clustering) a set of records corresponding to transactions of items into discrete segments so that different parts of the data show different kinds of trends. The clustering is used in order to create a segmentation of the data such that these trends are captured in each segment. Consequently, a different set of association rules are relevant for each segment. For a given customer, the segment to which he/she belongs most closely may be readily determined, and the trends in that segment may be used for generating the association rules.

Abstract: A system and method for generating itemset associations in a memory storage system comprising many transactions, with each transaction including one or more items capable of forming the itemset associations. The method involves generating a lexicographic tree structure having nodes representing itemset associations meeting a minimum support criteria. In a recursive manner, for each lexicographic least itemset (node) P of the lexicographic tree structure, candidate extensions of the node P are first determined. Then, the support of each of the candidate extensions is counted to determine frequent extension itemsets of that node P, while those itemsets not meeting a predetermined support criteria are eliminated. Child nodes corresponding to the frequent extensions and meeting the predetermined support criteria are created. For each frequent child of node P, all itemset associations for all descendants of node P are generated first. Thus, the lexicographic tree structure is generated in a depth first manner.

Abstract: The present invention derives product characterizations for products offered at an e-commerce site based on the text descriptions of the products provided at the site. A customer characterization is generated for any customer browsing the e-commerce site. The characterizations include an aggregation of derived product characterizations associated with products bought and/or browsed by that customer. A peer group is formed by clustering customers having similar customer characterizations. Recommendations are then made to a customer based on the processed characterization and peer group data.

Abstract: The present invention derives product characterizations for products offered at an e-commerce site based on the text descriptions of the products provided at the site. A customer characterization is generated for any customer browsing the e-commerce site. The characterizations include an aggregation of derived product characterizations associated with products bought and/or browsed by that customer. A peer group is formed by clustering customers having similar customer characterizations. Recommendations are then made to a customer based on the processed characterization and peer group data.

Abstract: A method for automatically generating associations of items included in a database. A user first specifies a support criteria indicating a strength of desired associations of items contained in the said database. Then, a recursive program is executed for generating a hierarchical tree structure comprising one or more levels of database itemsets, with each itemset representing item associations determined to have satisfied the specified support criteria.

Abstract: A VOD scheduler maintains a queue of pending performance for each video. Using the notion of queue selection factor, a batching policy is devised that schedules the video with the highest selection factor. Selection factors are obtained by applying discriminatory weighting factors to the adjusted queue lengths associated with each video where the weight decreases as the popularity of the respective video increases and the queue length is adjusted to take defection into account.