Abstract: Systems and methods are provided for identifying unsolicited or unwanted electronic communications, such as spam. The disclosed embodiments also encompass systems and methods for selecting content items from a content item database. Consistent with certain embodiments, computer-implemented systems and methods may use a clustering based statistical content matching anti-spam algorithm to identify and filter spam. Such a anti-spam algorithm may be implemented to determine a degree of similarity between an incoming e-mail with a collection of one or more spam e-mails stored in a database. If the degree of similarity exceeds a predetermined threshold, the incoming e-mail may be classified as spam. Further, in accordance with other embodiments, systems and methods may be provided to determine a degree of similarity between a query or search string from a user and content items stored in a database.

Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided for generating a reputation record and filtering electronic messages, each reputation record including a reputation score and a reputation key. The method includes receiving at least one incoming event notification, including a reputation key; determining, based on the reputation key, whether a corresponding reputation record exists; creating a new reputation record if the corresponding reputation record does not exist; determining a trust determination function based on the incoming event notification; calculating a reputation score based on the determined trust determination function, the incoming event notification, and an attribute associated with the reputation key; storing the calculated reputation score along with the reputation key in either the new reputation record or the corresponding reputation record; and filtering one or more electronic messages based on the calculated reputation score.

Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided for generating a reputation record and filtering electronic messages, each reputation record including a reputation score and a reputation key. The method includes receiving at least one incoming event notification, including a reputation key; determining, based on the reputation key, whether a corresponding reputation record exists; creating a new reputation record if the corresponding reputation record does not exist; determining a trust determination function based on the incoming event notification; calculating a reputation score based on the determined trust determination function, the incoming event notification, and an attribute associated with the reputation key; storing the calculated reputation score along with the reputation key in either the new reputation record or the corresponding reputation record; and filtering one or more electronic messages based on the calculated reputation score.

Abstract: The wireless non-contact switch detects movement of human body in the beam-shaped detection are which extends from the upper area on the wall toward the floor surface, and controls opening and closing of the automatic door. Regardless of the height of the location of the movement, as long as it is in the detection area, the switch detects the movement of different height location in the detection area. Therefore, regardless of the difference of regulation between each states, it can be operated at any height of the movement.

Abstract: The wireless non-contact switch detects movement of human body in the beam-shaped detection are which extends from the upper area on the wall toward the floor surface, and controls opening and closing of the automatic door. Regardless of the height of the location of the movement, as long as it is in the detection area, the switch detects the movement of different height location in the detection area. Therefore, regardless of the difference of regulation between each states, it can be operated at any height of the movement.

Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided for generating a reputation record and filtering electronic messages, each reputation record including a reputation score and a reputation key. The method includes receiving at least one incoming event notification, including a reputation key; determining, based on the reputation key, whether a corresponding reputation record exists; creating a new reputation record if the corresponding reputation record does not exist; determining a trust determination function based on the incoming event notification; calculating a reputation score based on the determined trust determination function, the incoming event notification, and an attribute associated with the reputation key; storing the calculated reputation score along with the reputation key in either the new reputation record or the corresponding reputation record; and filtering one or more electronic messages based on the calculated reputation score.

Abstract: Systems and methods are provided for identifying unsolicited or unwanted electronic communications, such as spam. The disclosed embodiments also encompass systems and methods for selecting content items from a content item database. Consistent with certain embodiments, computer-implemented systems and methods may use a clustering based statistical content matching anti-spam algorithm to identify and filter spam. Such a anti-spam algorithm may be implemented to determine a degree of similarity between an incoming e-mail with a collection of one or more spam e-mails stored in a database. If the degree of similarity exceeds a predetermined threshold, the incoming e-mail may be classified as spam. Further, in accordance with other embodiments, systems and methods may be provided to determine a degree of similarity between a query or search string from a user and content items stored in a database.

Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided for generating a reputation record and filtering electronic messages, each reputation record including a reputation score and a reputation key. The method includes receiving at least one incoming event notification, including a reputation key; determining, based on the reputation key, whether a corresponding reputation record exists; creating a new reputation record if the corresponding reputation record does not exist; determining a trust determination function based on the incoming event notification; calculating a reputation score based on the determined trust determination function, the incoming event notification, and an attribute associated with the reputation key; storing the calculated reputation score along with the reputation key in either the new reputation record or the corresponding reputation record; and filtering one or more electronic messages based on the calculated reputation score.

Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided for generating a reputation record and filtering electronic messages, each reputation record including a reputation score and a reputation key. The method includes receiving at least one incoming event notification, including a reputation key; determining, based on the reputation key, whether a corresponding reputation record exists; creating a new reputation record if the corresponding reputation record does not exist; determining a trust determination function based on the incoming event notification; calculating a reputation score based on the determined trust determination function, the incoming event notification, and an attribute associated with the reputation key; storing the calculated reputation score along with the reputation key in either the new reputation record or the corresponding reputation record; and filtering one or more electronic messages based on the calculated reputation score.