Abstract:
Disclosed is a transfer learning system for a deep neural network. The transfer learning system includes a pre-trained model storage unit configured to store a plurality of pre-trained models that are deep neural network models learned using one or more pre-training datasets, a transfer learning data input unit configured to receive transfer learning data, a pre-trained model selecting unit configured to select a pre-trained model corresponding to the transfer learning data from among the plurality of stored pre-trained models, and a transfer learning unit configured to generate one or more transfer learning models by performing transfer learning using the selected pre-trained model and the transfer learning data.
Abstract:
An automatic configuration device, for an Internet-of-Things (IoT) device, which operates a data analysis-based automation system includes when various types of IoT devices are registered in a system, a data analysis-based automation system for supporting both use of functions of the IoT devices and an effective analysis of collected data.
Abstract:
Provided are an adaptive knowledge base construction system and method. The adaptive knowledge base construction system includes a machine learning engine analyzing a correlation between pieces of data included in a first data set in a process of learning the first data set input thereto, based on machine learning, a rule generator generating a rule based on the machine learning by using an analysis result obtained by analyzing the correlation, and a semantic rule generator generating a semantic rule from the rule based on the machine learning by using a language expressing ontology, and reflecting the generated semantic rule in a knowledge base to extend the knowledge base.
Abstract:
A method and system for recommending a thing based on quality of service in a web of things environment, the method including (a) obtaining web log data and metadata of at least one thing; (b) computing QoS (Quality of Service) features of the thing from the web log data and metadata; (c) in response to obtaining user's review information on the thing, computing QoS grade information on the thing from the review information; and (d) generating a rule for predicting a QoS grade for a thing for which there is no user's review information with reference to the QoS grade information on the thing and the QoS features of the thing.
Abstract:
A method of filtering content including privacy information in an Internet of things (IoT) terminal includes generating, by the processor, content management data prescribing a mapping relationship between pieces of content, a kind of a network, and a plurality of applications and storing the content management data in a content management data storage unit, based on a user input, the content management data prescribing a security policy associated with external transmission of the pieces of content, and when an external transmission request message corresponding to specific content of the pieces of content is received from the specific application, determining, by the processor, whether to allow external transmission of the specific content in response to the external transmission request message, based on the security policy prescribed in the content management data.
Abstract:
An apparatus for generating IoT data is disclosed. The apparatus may search for a real IoT sensor capable of providing real IoT data desired by the user, collect the real IoT data desired by the user from the found real IoT sensor, and provide the collected real IoT data to the user. Also, when the real IoT sensor capable of providing the real IoT data desired by the user is not found, the apparatus may search for a realistic IoT sensor similar to the real IoT sensor, perform machine learning on the IoT data collected from the found realistic IoT sensor to generate realistic IoT data similar to the real IoT data, and provide the generated realistic IoT to the user.