Abstract: A governing modeling system maintains information associated with an analytic model. One or more policies may be defined that are associated with the analytic model and one or more instances of the analytic model. The system may monitor the analytic model and the one or more instances of the analytic model based on at least some of the information, the one or more policies associated with the analytic model and the one or more policies associated with the one or more instances of the analytic model.

Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: A governing modeling system maintains information associated with an analytic model. One or more policies may be defined that are associated with the analytic model and one or more instances of the analytic model. The system may monitor the analytic model and the one or more instances of the analytic model based on at least some of the information, the one or more policies associated with the analytic model and the one or more policies associated with the one or more instances of the analytic model.

Abstract: Demographic and transaction data are presented in a report usable for marketing-related purposes and other applications using a camera apparatus to capture customer image data at a point-of-sale location and sends the image data to a customer image database where the image data is stored. Demographic data (such as gender, age group, height) are extracted from the customer image data and sent to the customer image database. Point-of-sale transaction data is collected and sent to a transaction database where the transaction data is stored. A computer processes customer image data, transaction data, and attributes relating to the customer image data and transaction data, to correlate extracted demographic data to transaction data. The correlated data is preferably sent to a target marketing database and used to generate a market research report.

Abstract: Method, apparatus and system for location evaluation and site selection, capable of effectively configuring the site network and evaluating the facility location by scientifically modeling and incorporating human knowledge are provided. In one aspect, geographic and demographic data associated with a plurality of locations and human knowledge comprising partial rating knowledge and pair-wise preference knowledge are used in a regression algorithm to construct a location evaluation model. The regression algorithm is further refined using active learning that identifies a plurality of pairs of locations to improve precision of the regression algorithm.

Abstract: Demographic and transaction data are presented in a report usable for marketing-related purposes and other applications using a camera apparatus to capture customer image data at a point-of-sale location and sends the image data to a customer image database where the image data is stored. Demographic data (such as gender, age group, height) are extracted from the customer image data and sent to the customer image database. Point-of-sale transaction data is collected and sent to a transaction database where the transaction data is stored. A computer processes customer image data, transaction data, and attributes relating to the customer image data and transaction data, to correlate extracted demographic data to transaction data. The correlated data is preferably sent to a target marketing database and used to generate a market research report.

Abstract: Demographic and transaction data are presented in a report usable for marketing-related purposes and other applications using a camera apparatus to capture customer image data at a point-of-sale location and sends the image data to a customer image database where the image data is stored. Demographic data (such as gender, age group, height) are extracted from the customer image data and sent to the customer image database. Point-of-sale transaction data is collected and sent to a transaction database where the transaction data is stored. A computer processes customer image data, transaction data, and attributes relating to the customer image data and transaction data, to correlate extracted demographic data to transaction data. The correlated data is preferably sent to a target marketing database and used to generate a market research report.

Abstract: Demographic and transaction data are presented in a report usable for marketing-related purposes and other applications using a camera apparatus to capture customer image data at a point-of-sale location and sends the image data to a customer image database where the image data is stored. Demographic data (such as gender, age group, height) are extracted from the customer image data and sent to the customer image database. Point-of-sale transaction data is collected and sent to a transaction database where the transaction data is stored. A computer processes customer image data, transaction data, and attributes relating to the customer image data and transaction data, to correlate extracted demographic data to transaction data. The correlated data is preferably sent to a target marketing database and used to generate a market research report.

Abstract: Demographic and transaction data are presented in a report usable for marketing-related purposes and other applications using a camera apparatus to capture customer image data at a point-of-sale location and sends the image data to a customer image database where the image data is stored. Demographic data (such as gender, age group, height) are extracted from the customer image data and sent to the customer image database. Point-of-sale transaction data is collected and sent to a transaction database where the transaction data is stored. A computer processes customer image data, transaction data, and attributes relating to the customer image data and transaction data, to correlate extracted demographic data to transaction data. The correlated data is preferably sent to a target marketing database and used to generate a market research report.

Abstract: Various embodiments for maintaining security and confidentiality of data and operations within a fraud detection system. Each of these embodiments utilizes a secure architecture in which: (1) access to data is limited to only approved or authorized entities; (2) confidential details in received data can be readily identified and concealed; and (3) confidential details that have become non-confidential can be identified and exposed.

Abstract: A procedure for clustering documents that operates in high dimensions, processes tens of thousands of documents and groups them into several thousand clusters or, by varying a single parameter, into a few dozen clusters. The procedure is specified in two parts: computing a similarity score representing the k most similar documents (typically the top ten) for each document in the collection, and grouping the documents into clusters using the similarly scores.

Abstract: A lightweight document matcher employs minimal processing and storage. The lightweight document matcher matches new documents to those stored in a database. The matcher lists, in order, those stored documents that are most similar to the new document. The new documents are typically problem statements or queries, and the stored documents are potential solutions such as FAQs (Frequently Asked Questions). Given a set of documents, titles, and possibly keywords, an automatic back-end process constructs a global dictionary of unique keywords and local dictionaries of relevant words for each document. The application front-end uses this information to score the relevance of stored documents to new documents. The scoring algorithm uses the count of matched words as a base score, and then assigns bonuses to words that have high predictive value. It optionally assigns an extra bonus for a match of words in special sections, e.g., titles.

Abstract: A text categorization method automatically classifies electronic documents by developing a single pooled dictionary of words for a sample set of documents, and then generating a decision tree model, based on the pooled dictionary, for classifying new documents. Adaptive resampling techniques are applied to improve the accuracy of the decision tree model.