Abstract: A lifetime prediction method for nitride semiconductor light-emitting element that is a method for predicting lifetime of a nitride semiconductor light-emitting element, the method including a model creation step of creating a trained model by learning at least a correlation of at least one of a composition parameter or a physical property parameter of a layer constituting the nitride semiconductor light-emitting element and a manufacturing condition parameter, relative to lifetime of the nitride semiconductor light-emitting element; and a lifetime prediction step of predicting lifetime using the trained model. In the model creation step, at least one of the composition parameter or the physical property parameter of a predetermined layer of the nitride semiconductor light-emitting element is used for the learning, and a growth temperature of the predetermined layer is used as the manufacturing condition parameter for the learning.

Abstract: A light output prediction method for nitride semiconductor light-emitting element that is a method for predicting light output of a nitride semiconductor light-emitting element, the method including a model creation step of creating a trained model by learning at least a correlation of at least one of a composition parameter or a physical property parameter of a layer constituting the nitride semiconductor light-emitting element and a manufacturing condition parameter, relative to light output of the nitride semiconductor light-emitting element; and a light output prediction step of predicting light output using the trained model. In the model creation step, at least one of the composition parameter or the physical property parameter of a predetermined layer of the nitride semiconductor light-emitting element is used for the learning, and a growth temperature of the predetermined layer is used as the manufacturing condition parameter for the learning.

Abstract: A mail server identifies first keyword set including a keyword that is not included in a second keyword set, the key word being a keyword that appear in mail data with a frequency higher than a predetermined frequency, the mail data being extracted based on the second keyword set including a keyword used in extraction conditions of the mail data. Then, the mail server adds the first keyword set to the extraction conditions of the mail data.

Abstract: A mail server displays a list of mail addresses of the sources of mails matching with an extraction condition for inappropriate mails, the list being classified into levels which are divided according to the transmission status of mails matching with the extraction condition for each mail address. Then, in response to the selection of one of the mail addresses from the displayed list, the mail server displays the transition of the transmission status of the mails which match with the extraction condition and have the selected mail address.

Abstract: A mail server identifies first keyword set including a keyword that is not included in a second keyword set, the key word being a keyword that appear in mail data with a frequency higher than a predetermined frequency, the mail data being extracted based on the second keyword set including a keyword used in extraction conditions of the mail data. Then, the mail server adds the first keyword set to the extraction conditions of the mail data.

Abstract: A mail server displays a list of mail addresses of the sources of mails matching with an extraction condition for inappropriate mails, the list being classified into levels which are divided according to the transmission status of mails matching with the extraction condition for each mail address. Then, in response to the selection of one of the mail addresses from the displayed list, the mail server displays the transition of the transmission status of the mails which match with the extraction condition and have the selected mail address.

Abstract: To provide a technology indicating guidance for a usage method of information equipment and for solving an abnormality of the information equipment to not only users having knowledge about terminology of the information equipment but also users having none of the knowledge about the terminology of the information equipment. A guidance apparatus receives identifying information of information equipment from a device, reads an image from a database containing images about the information equipment with respect to the received identifying information, creates guidance information containing the read image, transmits the created guidance information to the device, receives information determined by a manipulation about the guidance information on the device, and controls so as to read the image used next for the guidance information from the received information.

Abstract: To provide a technology indicating guidance for a usage method of information equipment and for solving an abnormality of the information equipment to not only users having knowledge about terminology of the information equipment but also users having none of the knowledge about the terminology of the information equipment. A guidance apparatus receives identifying information of information equipment from a device, reads an image from a database containing images about the information equipment with respect to the received identifying information, creates guidance information containing the read image, transmits the created guidance information to the device, receives information determined by a manipulation about the guidance information on the device, and controls so as to read the image used next for the guidance information from the received information.

Abstract: In the present invention, information for content, software or both that a user set as a desired operation target of a content search rank changing process is stored in a operation target management table. Information for software active during a content search processing is stored in a currently active software management table. In case the content or software relates to the retrieved content as search results is present in the operation target management table or the currently active software management table, the relevancy rating of the retrieved content is calculated by adding a prescribed value to the relevancy rating of the retrieved content. Then, the retrieved content is sorted based on the relevancy rating and outputted in order sorted at a display device.

Abstract: In the present invention, information for content, software or both that a user set as a desired operation target of a content search rank changing process is stored in a operation target management table. Information for software active during a content search processing is stored in a currently active software management table. In case the content or software relates to the retrieved content as search results is present in the operation target management table or the currently active software management table, the relevancy rating of the retrieved content is calculated by adding a prescribed value to the relevancy rating of the retrieved content. Then, the retrieved content is sorted based on the relevancy rating and outputted in order sorted at a display device.

Abstract: The information categorizing apparatus comprises a feature element extraction section which extracts a feature element for each categorizing category from a plurality of sample texts included in the categorizing sample data in which a sample text group and a plurality of categories are associated with each other in advance. Further, a categorizing method determination section determines a categorizing method based on the categorizing sample data. A categorizing learning information generation section generates categorizing learning information representing a feature for each category, based on the extracted feature elements, in accordance with the determined categorizing method. An automatic categorizing section categorizes a new text group to be categorized for each category, in accordance with the determined categorizing method and the categorizing learning information.

Abstract: The information categorizing apparatus comprises a feature element extraction section which extracts a feature element for each categorizing category from a plurality of sample texts included in the categorizing sample data in which a sample text group and a plurality of categories are associated with each other in advance. Further, a categorizing method determination section determines a categorizing method based on the categorizing sample data. A categorizing learning information generation section generates categorizing learning information representing a feature for each category, based on the extracted feature elements, in accordance with the determined categorizing method. An automatic categorizing section categorizes a new text group to be categorized for each category, in accordance with the determined categorizing method and the categorizing learning information.