Abstract: A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Abstract: An apparatus for generating a valid neural network architecture includes one or more processors, and a memory storing one or more programs which are configured to be executed by the one or more processors. The one or more programs include instructions for a neural network architecture parser and a neural network architecture generator, which the a neural network architecture parser configured to generate one or more abstract syntax trees corresponding to neural network architectures, respectively, by parsing one or more neural network architectures; and a neural network architecture generator configured to generate one or more new neural network architectures by substituting at least a portion of blocks of the abstract syntax tree with blocks compatible with the partial regions.

Abstract: A neural network architecture embedding method according to an embodiment is performed by a computing device including one or more processors and a memory storing one or more programs executed by the one or more processors. The method generates a word data set for each of a plurality of layers of a neural network architecture on basis of one or more features of each of the plurality of layers, generates a graph regarding the neural network architecture on basis of the word data set and connection relationship between the plurality of layers, and generates a neural network architecture embedding vector for the neural network architecture by inputting the graph regarding the neural network architecture to a pre-trained network-vector transformation model.

Abstract: A data prediction method based on generative adversarial network (GAN) may be performed by a computing device. The data prediction method may include pre-training a generator neural network based on an auto encoder structure including an encoder and a decoder, and training a GAN including a discriminator neural network and the pre-trained generator neural network by a transfer learning method, wherein training the GAN by a transfer learning method includes training the GAN while fixing a decoder neural network of the generator neural network to the pre-trained initial state.

Abstract: A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Abstract: A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Abstract: A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Abstract: A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Abstract: An automated WLAN radio map construction method and system is provided. The automated WLAN radio map construction method includes: collecting WLAN fingerprints obtained by mobile device in an indoor space, machine-learning a learning model which is generated based on a state diagram in which divided areas of an indoor map are expressed by location states, arranging the collected WLAN fingerprints in corresponding location states, and storing a result of the arranging. Accordingly, collection locations of WLAN fingerprints collected in a plurality of unspecific smartphones without reference location information such as GPS signals can be automatically labeled.

Abstract: An automated WLAN radio map construction method and system is provided. The automated WLAN radio map construction method includes: collecting WLAN fingerprints obtained by mobile device in an indoor space, machine-learning a learning model which is generated based on a state diagram in which divided areas of an indoor map are expressed by location states, arranging the collected WLAN fingerprints in corresponding location states, and storing a result of the arranging. Accordingly, collection locations of WLAN fingerprints collected in a plurality of unspecific smartphones without reference location information such as GPS signals can be automatically labeled.

Abstract: A method of implementing a location-based service within a building is provided. The method includes receiving, from at least one electronic device, a plurality of data sets indicating information of wireless signals which the at least one electronic device measures for each time or for each location within the building; determining a similarity between the plurality of data sets; generating a logical path by integrating similar data sets; and generating a wireless signal map within the building by mapping the logical path to a physical path of the building.

Abstract: A method of implementing a location-based service within a building is provided. The method includes receiving, from at least one electronic device, a plurality of data sets indicating information of wireless signals which the at least one electronic device measures for each time or for each location within the building; determining a similarity between the plurality of data sets; generating a logical path by integrating similar data sets; and generating a wireless signal map within the building by mapping the logical path to a physical path of the building.