Abstract: A system and method is disclosed for collecting website visitor activity for profiling visitor interests and dynamically modifying the content of the website to better match the visitor's profile. The visitor activity data is collected directly from the visitor's client browser or from the website's own web log information. The collected data consists of the page identifier, page links, and the previous page identifier. Similarly, the modified page content can be sent directly to the client browser or can be sent back to the website server for integration with the other page content. The collected data is stored in a database. Based on the amount of information collected on the visitor and the various items that are presented on the website, the visitors and items are profiled so that a visitor's response to other items can be predicted and recommended to the visitor.

Abstract: A system and method for tracking subject behavior and making object recommendations include a data collection module that captures subject behavior and provides behavioral context for the recommendations; a profiling module that extracts characteristics of subjects and objects from the behavior data; and a recommendation module, which uses the profiles and the behavior context to generate personalized content and which includes a behavioral recommendation module, correlating profiles or uses other unconstrained methods for matching objects to subjects; a business rule module filtering and modifying recommendations by applying application-specific business logic to defined attributes of the objects; and a promotion module modifying the scores from the recommendation module to bias the recommendations towards certain objects based on additional business goals.

Abstract: A system and method is disclosed which predicts the relative occurrence or presence of an event or item based on sample data consisting of samples which contain and samples which do not contain the event or item. The samples also consist of any number of descriptive attributes, which may be continuous variables, binary variables, or categorical variables. Given the sampled data, the system automatically creates statistically optimal segments from which a functional input/output relationship can be derived. These segments can either be used directly in the form of a lookup table or in some cases as input data to a secondary modeling system such as a linear regression module, a neural network, or other predictive system.

Abstract: A system and method is disclosed for profiling subjects and objects based on subjects' responses to various objects, for purposes of determining and presenting the objects most likely to generate the most likely response from each visitor. Object ratings are explicitly submitted by subjects or derived implicitly from visitor interactions with the objects. A profiling engine processes the ratings information and generates compact profiles of each subject and object based on similarities and differences in affinities between the group of subjects and the group of objects. The object profiles can be clustered to create behavioral object categories. Additionally, a modeling module inverts the abstract subject and object profiles into marketing attributes. The system has application in market analysis and segmentation, behavioral targeting, product placement, and online advertising, to name but a few applications.

Abstract: A system and method is disclosed for collecting website visitor activity for profiling visitor interests and dynamically modifying the content of the website to better match the visitor's profile. The visitor activity data is collected directly from the visitor's client browser or from the website's own web log information. The collected data consists of the page identifier, page links, and the previous page identifier. Similarly, the modified page content can be sent directly to the client browser or can be sent back to the website server for integration with the other page content. The collected data is stored in a database. Based on the amount of information collected on the visitor and the various items that are presented on the website, the visitors and items are profiled so that a visitor's response to other items can be predicted and recommended to the visitor.

Abstract: A system and method is disclosed for generating targeted e-mails based on individual subject behavior and interests, as determined by an application's website browsing behavior, online and offline purchases, ratings, and other implicit and explicit indications of subject preferences and interests. The subject's behavior data is collected directly from the subject's client browser or from the application's own information and used to generate profiles of the subjects that will be sent e-mails and the objects that will be recommended. Targeted content is generated by matching subject and object profiles in combination with any subject segmentation filters that the application provides. The e-mail targeting is optimized by measuring subject response to targeted e-mails and adjusting recommendation strategies used to generate subsequent recommendations.

Abstract: A system and method is disclosed for profiling a subject's search engine keywords and results based on relevancy feedback. Because the system is based on the search behavior of the user, the profiling is language independent and balances the specificity of search terms against the profiled interests of the user. The system can also score keywords on their search effectiveness and eliminate ineffective keywords from the keyword index. The system can also synthesize new keyword combinations to assist the user in refining the search or acquiring related content. The system has application in text mining, personalization, behavioral search, search engine optimization, and content acquisition, to name but a few applications.

Abstract: A system and method is disclosed which predicts the relative occurrence or presence of an event or item based on sample data consisting of samples which contain and samples which do not contain the event or item. The samples also consist of any number of descriptive attributes, which may be continuous variables, binary variables, or categorical variables. Given the sampled data, the system automatically creates statistically optimal segments from which a functional input/output relationship can be derived. These segments can either be used directly in the form of a lookup table or in some cases as input data to a secondary modeling system such as a linear regression module, a neural network, or other predictive system.

Abstract: A system and method is disclosed which predicts the relative occurrence or presence of an event or item based on sample data consisting of samples which contain and samples which do not contain the event or item. The samples also consist of any number of descriptive attributes, which may be continuous variables, binary variables, or categorical variables. Given the sampled data, the system automatically creates statistically optimal segments from which a functional input/output relationship can be derived. These segments can either be used directly in the form of a lookup table or in some cases as input data to a secondary modeling system such as a linear regression module, a neural network, or other predictive system.

Abstract: A system and method is disclosed for allocating servers across a large number of applications and for providing a predictable and consistent service response under conditions where the use of the service and associated loads is driven by unknown factors. The invention provides fault tolerance within an application through multiple resources per application and fault tolerance across applications by limiting the overlap in resources between applications. The computational load on the service may include both individual processing time due to the complexity of a single request and the number of requests. Complexity may be unpredictable because the service is self-provisioned and may allow service users to create an arbitrary sequence of compound processing steps. The number of requests may vary due to a variety of events, including daily, seasonal, or holidays, or factors driven more directly by the user of the service, such as sales, advertising, or promotions.

Abstract: A system and method is disclosed for profiling a subject's search engine keywords and results based on relevancy feedback. Because the system is based on the search behavior of the user, the profiling is language independent and balances the specificity of search terms against the profiled interests of the user. The system can also synthesize new keyword combinations to assist the user in refining the search or acquiring related content. The system has application in text mining, personalization, behavioral search, search engine optimization, and content acquisition, to name but a few applications.

Abstract: A system and method is disclosed for monitoring human interactions, including transactions and communications, profiling the subject and objects in those interactions, and comparing subject profiles to profiles of subjects with known characteristics to determine whether the test subject is normal or abnormal subjects. The behavior data can be collected electronically in a virtual environment, such as a website, through video surveillance, card access, phone records, purchase histories, or any other consistent identified record of behavior. The invention has application in detecting various types of unusual and malicious activity, including spam, viruses, terrorism, identity theft, and money laundering, to name but a few applications.

Abstract: A system and method is disclosed for profiling subjects and objects based on subjects' responses to various objects for purposes of determining and presenting the objects most likely to generate the most positive response from each visitor. Object ratings, such as aesthetic response, preference, interest, or relevancy, are explicitly submitted by subjects or derived implicitly from visitor interactions with the objects. Objects include movies, books, songs, commercial products, news articles, advertisements or any other type of content or physical item. A profiling engine processes the ratings information and generates compact profiles of each subject and object based on the similarities and differences in affinities between the group of subjects and the group of objects. A recommendation engine then generates recommendations to a subject based on similarity between the subject and object profiles. The recommendation engine can also match subjects to other subjects and objects to other objects.

Abstract: A system and method is disclosed which predicts the relative occurrence or presence of an event or item based on sample data consisting of samples which contain and samples which do not contain the event or item. The samples also consist of any number of descriptive attributes, which may be continuous variables, binary variables, or categorical variables. Given the sampled data, the system automatically creates statistically optimal segments from which a functional input/output relationship can be derived. These segments can either be used directly in the form of a lookup table or in some cases as input data to a secondary modeling system such as a linear regression module, a neural network, or other predictive system.

Abstract: A system and method is disclosed for allocating servers across a large number of applications and for providing a predictable and consistent service response under conditions where the use of the service and associated loads is driven by unknown factors. The invention provides fault tolerance within an application through multiple resources per application and fault tolerance across applications by limiting the overlap in resources between applications. The computational load on the service may include both individual processing time due to the complexity of a single request and the number of requests. Complexity may be unpredictable because the service is self-provisioned and may allow service users to create an arbitrary sequence of compound processing steps. The number of requests may vary due to a variety of events, including daily, seasonal, or holidays, or factors driven more directly by the user of the service, such as sales, advertising, or promotions.

Abstract: A computer implemented web-based system and computer implemented web-based method is disclosed for recording, repeated transactions of objects or groups of objects by subjects, utilizing the duration between transactions to predict the next transaction time of an object by a subject, and recommending the object to the subject based on the predicted next transaction time. The system can also classify object according to their replenishment behavior and make product recommendations based on the class of objects a subject shows interest in. Objects include movies, books, songs, commercial products, news articles, advertisements or any other type of content or physical item. The system has application in personalization, behavioral targeting, Internet retailing, and interactive radio, to name but a few applications.

Abstract: A system and method is disclosed for profiling a subject's search engine keywords and results based on relevancy feedback. Because the system is based on the search behavior of the user, the profiling is language independent and balances the specificity of search terms against the profiled interests of the user. The system can also score keywords on their search effectiveness and eliminate ineffective keywords from the keyword index. The system can also synthesize new keyword combinations to assist the user in refining the search or acquiring related content. The system has application in text mining, personalization, behavioral search, search engine optimization, and content acquisition, to name but a few applications.

Abstract: A system and method is disclosed for monitoring human interactions, including transactions and communications, profiling the subject and objects in those interactions, and comparing subject profiles to profiles of subjects with known characteristics to determine whether the test subject is normal or abnormal subjects. The behavior data can be collected electronically in a virtual environment, such as a website, through video surveillance, card access, phone records, purchase histories, or any other consistent identified record of behavior. The invention has application in detecting various types of unusual and malicious activity, including spam, viruses, terrorism, identity theft, and money laundering, to name but a few applications.

Abstract: A system and method is disclosed for generating targeted e-mails based on individual subject behavior and interests, as determined by an application's website browsing behavior, online and offline purchases, ratings, and other implicit and explicit indications of subject preferences and interests. The subject's behavior data is collected directly from the subject's client browser or from the application's own information and used to generate profiles of the subjects that will be sent e-mails and the objects that will be recommended. Targeted content is generated by matching subject and object profiles in combination with any subject segmentation filters that the application provides. The e-mail targeting is optimized by measuring subject response to targeted e-mails and adjusting recommendation strategies used to generate subsequent recommendations.

Abstract: A system and method is disclosed for profiling subjects and objects based on subjects' responses to various objects for purposes of determining and presenting the objects most likely to generate the most likely response from each visitor. Object ratings, such as aesthetic response, preference, interest, or relevancy, are explicitly submitted by subjects or derived implicitly from visitor interactions with the objects. Objects include movies, books, songs, commercial products, news articles, advertisements or any other type of content or physical item. A profiling engine processes the ratings information and generates compact profiles of each subject and object based on the similarities and differences in affinities between the group of subjects and the group of objects. The object profiles can be clustered to create behavioral object categories.