Abstract: A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price.

Abstract: An architecture is provided for a widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially include a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally; using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: An architecture is provided for a widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially include a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally; using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: An architecture is provided for a widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially include a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally; using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: A widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially consist of a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: A database system stores information about potential patients that allows medical professionals to gauge the legal risk presented by the potential patients, giving the medical professionals the opportunity to avoid medical involvement with those individuals most prone to engaging in unwarranted legal actions. The database may also be used by insurance companies, legal services and other professional service providers to screen for potentially litigious customers. Information in the database is processed to provide a risk assessment score for each patient that is used for screening purposes.

Abstract: A database system stores information about potential patients that allows medical professionals to gauge the legal risk presented by the potential patients, giving the medical professionals the opportunity to avoid medical involvement with those individuals most prone to engaging in unwarranted legal actions. The database may also be used by insurance companies, legal services and other professional service providers to screen for potentially litigious customers. Information in the database is processed to provide a risk assessment score for each patient that is used for screening purposes.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally; using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: An architecture is provided for a widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially include a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally, using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: A computer system is adapted to predict the likelihood, temporal (or developmental) state, possible location(s), rate of spread or “infectiousness”, etc. of a potential epidemic. A wide and diverse range of inputs and associated parameters are inputted into the system some of which may be statistically correlatable with certain hidden states including those which are temporally oriented disease stages of progression as well as other types of attributes. A Dynamic Bayesian Belief Network or other adaptive or machine learning method is used for the probabilistic analysis. The system statistically analyzes and reanalyzes the totality of all recently updated information (and within the context of all past information), as can efficiently be modeled by the Dynamic Bayesian Belief Network or other adaptive or machine learning method to provide updated predictions and to suggest a recommended reactive protocol to an epidemic.

Abstract: A widely distributed security system (SDI-SCAM) that protects computers at individual client locations, but which constantly pools and analyzes information gathered from machines across a network in order to quickly detect patterns consistent with intrusion or attack, singular or coordinated. When a novel method of attack has been detected, the system distributes warnings and potential countermeasures to each individual machine on the network. Such a warning may potentially consist of a probability distribution of the likelihood of an intrusion or attack as well as the relative probabilistic likelihood that such potential intrusion possesses certain characteristics or typologies or even strategic objectives in order to best recommend and/or distribute to each machine the most befitting countermeasure(s) given all presently known particular data and associated predicted probabilistic information regarding the prospective intrusion or attack.

Abstract: When individual persons or vehicles move through a transportation network, they are likely to be both actively and passively creating information that reflects their location and current behavior. In this patent, we propose a system that makes complete use of this information. First, through a broad web of sensors, our system collects and stores the full range of information generated by travelers. Next, through the use of previously-stored data and active computational analysis, our system deduces the identity of individual travelers. Finally, using advanced data-mining technology, our system selects useful information and transmits it back to the individual, as well as to third-party users; in short, it forms the backbone for a variety of useful location-related end-user applications.

Abstract: A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price.

Abstract: This document discloses the architecture and proposed application of a highly distributed network security system. Using a combination of intelligent client-side and server-side agents, redundant memory arrays, duplicate network connections, and a variety of statistical analytics, which are cleverly designed to anticipate, counteract and defeat likely strategic designs, behaviors and adaptations of these threats which may be intended to evade or even disable the network security system, this system serves to detect, prevent, and repair a wide variety of network intrusions.

Abstract: A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price.