Four Pi Systems Corporation

Kuhuro Investments Ag, L.l.c.

Aptex Software, Inc.

Gerald S Russell

Michael A Lazarus

John Andrew Adams

William Robert Caid

Matthias Blume

Robert L Corey

Kevin L Sitze

Bruce D Baker

Edward W Ross

Richard S Pugh

Frederique Vernhes

Larry S Peranich

Kenneth B Brown

Christopher S Sexton

Joel Lawrence Carleton

William R Caid

Bradley D Kindig

Kerry L Brown

David C Reynolds

Brian L Ganz

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.

Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching

A system and method for selecting and presenting personally targeted entities such as advertising, coupons, products and information content, based on tracking observed behavior on a user-by-user basis and utilizing an adaptive vector space representation for both information and behavior. The system matches users to entities in a manner that improves with increased operation and observation of user behavior. User behavior and entities (ads, coupons, products) and information (text) are all represented as content vectors in a unified vector space. The system is based on an information representation called content vectors that utilizes a constrained self organization learning technique to learn the relationships between symbols (typically words in unstructured text). Users and entities are each represented as content vectors.

System and method for optimal adaptive matching of users to most

A high resolution laminography system for the inspection of integrated circuits wherein a beam of highly focused electrons is traced in a circular pattern on a flat target within a vacuum chamber. The target converts the electron beam into X-rays, so that a source of X-rays is produced which rotates in synchronization with a rotating detector assembly. An object is placed within the vacuum chamber, between the X-ray source and the detector so that an X-ray cross sectional image of a cutting plane of the object is produced. A computer and feedback system controls image acquisition and an automated positioning system. The computer system can also operate under program control to automatically analyze data, measure characteristics of the object under inspection, and make decisions regarding the acceptability of the object's quality. The invention also employs a channeltron imager to directly image the target so that the condition of the target may be monitored, and electron drift within the system can be compensated for.

Method and apparatus for high resolution inspection of electronic items

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San Diego, CA, United States of America

Gerald S Russell