Abstract: A triple verification method is provided.

Abstract: Provided is an incorrect triple detection system including a triple selector configured to select a target triple (subject, type, object) in a knowledge base, a sampler configured to create a sentence model by connecting object triples sharing entities included in the target triple, a model builder configured to embed the sentence model into a vector space to create a training entity vector and build an embedding model, and an incorrect triple detector configured to detect an incorrect triple by inputting a test triple into the embedding model.

Abstract: A terminal device for generating user behavior data, a method for generating user behavior data, and a recording medium are provided. The disclosed terminal device may include a memory unit storing instructions readable by a computer; and a processor unit implemented to execute the instructions, where the processor unit may compute a probability distribution model for achieving the intentions of a user by using raw data related to time-dependent actions of the user and may generate user behavior data by using the probability distribution model, with the user behavior data comprising time series data in which multiple actions composing the intentions of the user are aligned in order.

Abstract: A triple verification method is provided.

Abstract: Provided is an incorrect triple detection system including a triple selector configured to select a target triple (subject, type, object) in a knowledge base, a sampler configured to create a sentence model by connecting object triples sharing entities included in the target triple, a model builder configured to embed the sentence model into a vector space to create a training entity vector and build an embedding model, and an incorrect triple detector configured to detect an incorrect triple by inputting a test triple into the embedding model.

Abstract: Provided are a system and method for automatically recreating personal media through fusion of multimodal features. The system includes a multimodal fusion analyzer configured to analyze semantics of personal media having various forms based on a plurality of modalities and divide the personal media into media fragments which are the smallest units having semantics, a semantic-based intelligent retriever configured to store and retrieve the divided media fragments by considering the semantics, a personal media recommender configured to learn and analyze a profile of a user through modeling the user, and select and recommend a plurality of media fragments wanted by the user among the media fragments retrieved by the semantic-based intelligent retriever, and a personal media creator configured to create new personal media using the plurality of media fragments recommended by the personal media recommender according to a scenario input by the user.

Abstract: A terminal device for generating user behavior data, a method for generating user behavior data, and a recording medium are provided. The disclosed terminal device may include a memory unit storing instructions readable by a computer; and a processor unit implemented to execute the instructions, where the processor unit may compute a probability distribution model for achieving the intentions of a user by using raw data related to time-dependent actions of the user and may generate user behavior data by using the probability distribution model, with the user behavior data comprising time series data in which multiple actions composing the intentions of the user are aligned in order.

Abstract: Disclosed are ontology-based reasoning apparatus, system, and method using user-defined rules. The ontology-based reasoning apparatus includes a memory storing two or more triple data; and a processor connected to the memory, in which the processor parses user-defined rules input from a user in ontology-based rules to generate a plurality of condition meta information corresponding to a plurality of conditions included in a condition section of the user-defined rules and one result meta information corresponding to one result included in a conclusion section of the user-defined rules, retrieves a plurality of triple data in two or more triple data prestored using the plurality of condition meta information, and reasons new triple data from the plurality of triple data retrieved using the result meta information to store the reasoned new triple data in the memory.

Abstract: Disclosed are a method of operating a knowledgebase and a server using the same. The method of operating a knowledgebase may include: (a) receiving triple data sets as input; (b) forming at least one data cluster set by classifying the triple data sets according to relation based on semantic information of the knowledgebase; and (c) learning each relation model by inputting the data cluster set into a neural tensor network.

Abstract: Ontology reasoning method and apparatus are disclosed. The ontology reasoning method comprises (a) broadcasting a schema triple to nodes; (b) partitioning triples other than the schema triple and distributing the partitioned triples to the nodes; and (c) reasoning at least one of the schema triple or the triples according to a reasoning rule and then renewing a confidence value of the reasoned triple.

Abstract: Ontology-based reasoning apparatus and method using knowledge of an expert are disclosed. The ontology-based reasoning apparatus includes an input unit through which a plurality of the knowledge of the expert including a condition and a result are inputted, a conversion unit configured to convert the inputted knowledge to ontology-based rules, and a reasoning performing unit configured to reason a conclusion by using the converted rules and generate an explanation of a rule corresponding to cause of the conclusion. Here, the rule includes a condition node corresponding to the condition, a result node corresponding to the result and an edge for connecting the condition node to the result node, the edge includes an edge direction and an edge value, and the edge value corresponds to an explanation about relation between the condition node and the result node.

Abstract: Provided are a system and method for automatically recreating personal media through fusion of multimodal features. The system includes a multimodal fusion analyzer configured to analyze semantics of personal media having various forms based on a plurality of modalities and divide the personal media into media fragments which are the smallest units having semantics, a semantic-based intelligent retriever configured to store and retrieve the divided media fragments by considering the semantics, a personal media recommender configured to learn and analyze a profile of a user through modeling the user, and select and recommend a plurality of media fragments wanted by the user among the media fragments retrieved by the semantic-based intelligent retriever, and a personal media creator configured to create new personal media using the plurality of media fragments recommended by the personal media recommender according to a scenario input by the user.

Abstract: A mobile device for distinguishing a user's movement, a method therefor, and a method for generating a hierarchical tree model therefor. Particularly, the mobile device includes: an acceleration sensor; a buffer for collecting the acceleration data outputted from the acceleration sensor according to a user's specific movement; an extraction unit for extracting the characteristic elements of the user's specific movement based on the acceleration data collected by the buffer; and a movement judgment unit for determining to which class the user's specific movement belongs by inputting the characteristic elements extracted by the extraction unit into a pre-structured hierarchical tree model, wherein the hierarchical tree model is pre-structured based on the characteristic elements extracted for each movement.

Abstract: A mobile device for distinguishing a user's movement, a method therefor, and a method for generating a hierarchical tree model therefor. Particularly, the mobile device includes: an acceleration sensor; a buffer for collecting the acceleration data outputted from the acceleration sensor according to a user's specific movement; an extraction unit for extracting the characteristic elements of the user's specific movement based on the acceleration data collected by the buffer; and a movement judgment unit for determining to which class the user's specific movement belongs by inputting the characteristic elements extracted by the extraction unit into a pre-structured hierarchical tree model, wherein the hierarchical tree model is pre-structured based on the characteristic elements extracted for each movement.

Abstract: There is provided a spatial reasoner for reasoning a topological relation and a directional relation between two geo-entities. The spatial reasoner includes a plurality of spatial knowledge bases in which spatial relations are defined; a spatial reasoning engine configured to infer new spatial relations through a cross consistency check of the spatial knowledge bases; and a query processing engine configured to answer to a spatial query using the new spatial relations inferred from the spatial reasoning engine. Therefore, it is possible to perform efficient and accurate spatial reasoning.

Abstract: Provided are a client and a server which filter errors in signal data collected in a wireless signal map creating process and increase accuracy of a signal map, and a wireless signal map creating system using the same. The wireless signal map creating system collects a local wireless signal map, stores a global wireless signal map, calculates a predicted signal strength of a specific point using a reception strength of at least one point located adjacent to the specific point in the local wireless signal map, compares a wireless signal strength of the specific point in the local wireless signal map and a predicted signal strength to determine an error or not, and updates the global wireless signal map based on a determination result.

Abstract: There is provided a method for recognizing a user context using multimodal sensors, and the method includes classifying accelerometer data by extracting candidates for movement feature from the accelerometer data collected from an accelerometer, selecting one or more movement features from the extracted candidates for movement feature based on relevance and redundancy thereof, and then inferring a user's movement type based on the selected movement features using a first time-series probability model; classifying audio data by extracting surrounding features from the audio data collected from an audio sensor and inferring the user's surrounding type based on the extracted surrounding features; and recognizing a user context by recognizing the user context based on either of the movement type or the surrounding type.

Abstract: Semiconductor devices and manufacturing methods thereof are provided. A semiconductor device can include a gate dielectric, a gate electrode, sidewall spacers, and source and drain regions. The gate electrode can include an electrode seed layer and an electrode metal layer. In another embodiment, the gate electrode can be formed of a deposited metal silicon layer.

Abstract: A semiconductor substrate includes a plurality of isolation regions formed therein and having a trench in a region between the isolation wells, a gate insulating layer formed within the trench, a gate electrode formed on the gate insulating layer filling the trench, and source and drain electrodes formed on the substrate between the gate electrode and the isolation wells.

Abstract: Disclosed is a method for providing an insulation trench on a semiconductor substrate. The method includes the steps of depositing a pad oxide layer and a nitride layer on a semiconductor substrate; etching the nitride layer and the pad oxide layer and depositing a first insulating layer; forming spacers along sidewalls of the pad oxide layer and the nitride layer by anisotropic etching the first insulating layer; forming trenches by etching the semiconductor substrate; forming a trench insulating layer pattern by depositing a second insulating layer and etching the same; and polishing the trench insulating layer pattern.