Patent application number | Description | Published |
20110038313 | ENHANCED COMMUNICATION APPARATUS FOR PROVIDING ENHANCED CONCATENATION, SEGMENTATION AND REASSEMBLY OF SERVICE DATA UNITS - Provided is an enhanced communication apparatus. The enhanced communication apparatus may enable a Packet Data Convergence Protocol (PDCP) layer unit to perform a part of a concatenation function, a segmentation function, and a reassembly function of a Radio Link Control (RLC) layer unit that is a sublayer of Layer 2, and may decrease a number of Packet Data Convergence Protocol Packet Data Units (PDCP PDUs) to be processed by the RLC layer unit. | 02-17-2011 |
20110078730 | METHOD AND APPARATUS FOR SCHEDULING RADIO ACCESS TO REDUCE CHANNEL ZAPPING DELAY - Provided is a method and apparatus for scheduling a radio access to reduce a channel zapping delay. The radio access scheduling method may receive abstract information with respect to all of currently receivable channels at each channel scheduling interval, and may receive the abstract information in advance and provide the abstract information when a channel change request is received, and thereby reduce the channel zapping delay. | 03-31-2011 |
20110143802 | PAGING MANAGEMENT METHOD AND SYSTEM FOR HOME EVOLVED BASE STATION - Provided is a paging management system that may transfer a paging message to only a small base station where a terminal is estimated to be positioned, and thereby decrease a traffic amount required to transfer the paging message. A paging management method may include: configuring a virtual tracking area by grouping a plurality of small base stations according to a position of a small base station accessed by a terminal; verifying a final small base station accessed by the terminal when a paging message is to be transmitted to the terminal; and transferring the paging message to small base stations of the virtual tracking area including the final small base station. | 06-16-2011 |
20110149905 | HANDOVER METHOD BETWEEN eNBs IN MOBILE COMMUNICATION SYSTEM - A method for processing a handover procedure in a mobile communication system includes: receiving a message having radio access bearer information for radio resource re-establishment and packet forwarding from a target base station; searching uplink (UL) packet forwarding indicator information included in the message including the radio access bearer information; and forwarding UL/DL packets at a source base station when the UL packet forwarding information is set to ON. The method further includes, when UL packet forwarding indicator is set to ON, having bitmap information, which indicates whether or not to receive uplink (UL) packet data convergence protocol (PDCP) SDU packets, in an SN status transfer message transmitted to the target base station from the source base station. | 06-23-2011 |
Patent application number | Description | Published |
20090100090 | DEVICE AND METHOD FOR AUTOMATICALLY GENERATING ONTOLOGY INSTANCE - The present invention relates to a method and device for generating an ontology instance that classifies documents into structured documents and unstructured documents and automatically generates ontology instances. The method includes collecting documents corresponding to classes of an ontology from Web; if the collected documents are unstructured documents, extracting inter-entity relationship information from the unstructured documents; if the collected documents are structured documents, extracting inter-entity relationship information from the structured documents; generating ontology instances from the extracted inter-entity relationship information, and mapping the generated ontology instances to corresponding classes of the ontology. | 04-16-2009 |
20100138712 | APPARATUS AND METHOD FOR VERIFYING TRAINING DATA USING MACHINE LEARNING - An apparatus for verifying training data using machine learning includes: a training data separation unit for separating provided initial training data into N training data and N verification data, where N is a natural number; a machine learning unit for performing machine learning on the separated training data to generate a training model; an automatic tagging unit for automatically tagging an original text of the verification data using the generated training model to provide automatic tagging results; and an error determination unit for comparing the verification data to the automatic tagging results to determine error candidates of the training data. | 06-03-2010 |
20100145922 | PERSONALIZED SEARCH APPARATUS AND METHOD - A personalized search apparatus includes: a model generating unit for generating a user favorites analysis model based on directory grouping information about directories stored in a user terminal and user behavior information; and a user favorites analysis model DB for storing the generated user favorites analysis model. Further, the personalized search apparatus includes a search engine for searching for a file relevant to an input query using an information search engine installed in the user terminal to generate search results; and a personalized search engine for re-ranking the search results generated by the search engine based on the user favorites analysis model to generate personalized search results. | 06-10-2010 |
20100145952 | ELECTRONIC DOCUMENT PROCESSING APPARATUS AND METHOD - An electronic document processing apparatus includes: a document set storage unit storing hash tables including hash values of documents to be processed; a content extraction unit for extracting body contents from a newly input electronic document; and a sentence separation unit for separating sentences from the extracted body contents. The apparatus further includes a duplicate document determination unit for converting the separated sentences into unique hash values by a hash algorithm, determining each of the separated checking if there is a duplicate sentence depending on whether or not there is a collision between the converted hash values and the hash values in the hash tables of the document set storage unit, and determining if the electronic document is a duplicate document based on the ratio of duplicate sentences to all of the sentences in the electronic document. | 06-10-2010 |
20110137919 | APPARATUS AND METHOD FOR KNOWLEDGE GRAPH STABILIZATION - A method for stabilizing a knowledge graph includes: generating a knowledge graph in which same entities in a semantic relation list between entities provided as an input are represented as a single node based on names and types of the entities; computing, on the knowledge graph, semantic similarities between all potential entity pairs of same entity types by comparing, for each potential entity pair, a type of relation associated with an entity in the entity pair and an opponent entity to the entity; and selecting, based on the semantic similarities, a representative entity from each of semantically similar entity pairs on the knowledge graph and integrating an opponent entity to the representative entity into the representative entity. The method further includes computing relation weighted values between the entities by using a graph analysis and statistic information, and adding the weighted values to the knowledge graph. | 06-09-2011 |
20110145264 | METHOD AND APPARATUS FOR AUTOMATICALLY CREATING ALLOMORPHS - A method of automatically creating allomorphs of a keyword, includes creating allomorph candidates of a search keyword using a user log and/or user session information when the search keyword is input; and extracting a related word for verification from a web document using a related word patter from to verify the allomorph candidates. Further, the method of automatically creating allomorphs of a keyword includes removing over-created and/or erroneous candidates from the allomorph candidates using the extracted related word for verification and creating allomorphs of the search keyword. | 06-16-2011 |
20120089584 | METHOD AND MOBILE TERMINAL FOR PERFORMING PERSONALIZED SEARCH - Provided are a method and mobile terminal for performing a personalized search, capable of providing search results optimized for a user in consideration of location and user preference. The method includes acquiring a question keyword from a user and information about the location of a mobile terminal, making a local search on the basis of the question keyword and the location information to generate local search results, displaying the local search results and storing a use record of the user of the mobile terminal corresponding to the displayed local search results, generating a user preference analysis model using the location information and the use record, then applying the generated user preference analysis model to the local search results, and deducing personalized final local search results from the local search results. Thus, it is possible to provide the local search results optimized for the user. | 04-12-2012 |
20120101807 | QUESTION TYPE AND DOMAIN IDENTIFYING APPARATUS AND METHOD - A question type and domain identifying apparatus includes: a question type identifier for recognizing the number of words of a user's question to identify whether the user's question is a query for performing information searching or a question for performing a question and answer (Q&A); a question domain distributor for distributing one of plural preset domain specialized Q&A engines, as a Q&A engine of the user's question based on the recognized word number; and a Q&A engine block, including the domain specialized Q&A engines, for selectively performing information searching or a Q&A with respect to the user's question in response to the distribution of the question domain distributor. | 04-26-2012 |
20130054553 | METHOD AND APPARATUS FOR AUTOMATICALLY EXTRACTING INFORMATION OF PRODUCTS - A method for automatically extracting information of products, includes searching documents based on product names; and extracting sentences including advantages and disadvantages for products having the product names from the searched documents. Further, the method for automatically extracting the information of the products includes classifying the sentences by similar contents among the extracted sentences; selecting representative sentences among the classified sentences; and calculating each weight of the selected representative sentences. | 02-28-2013 |