Abstract: Disclosed herein are a system for content recommendation service, a content recommendation device and a method of operating the same. The system can recommend personalized content directly related with a recommendation target, irrespectively of whether the content consumption history of the recommendation target user is sufficient to analyze the purchase/use pattern or whether there are other users having similar purchase/user pattern with the recommendation target user. As a result, the recommendation reliability can be improved.

Abstract: The present invention relates to the use of a plurality of dependency trees in tree-based statistical machine translation and proposes a dependency forest to effectively process the plurality of dependency trees. The present invention can improve a translation capability by generating a translation rule and a dependency language model by using the dependency forest and applying the generated translation rule and dependency language model when a source language text is converted to a target language text.

Abstract: The present invention relates to statistical machine translation, and provides a machine translation device and a machine translation method that acquire a creation probability for a target language from a single corpus while extracting respective conversion probabilities by extracting syntax conversion knowledge and word translation knowledge from a parallel corpus, model a weighted translation model by allowing each of the conversion knowledge and each of the probabilities to learn using a translation model learning device, and generate a target sentence through decoding processes of a syntax converter and a word translator by applying the translation model to a source sentence input in real time, thereby resolving disadvantages of the existing phrase-based SMT and syntax-based SMT and combining advantages thereof.

Abstract: Disclosed herein are a method for user intention profiling and an apparatus for the same. Behavior data may be created based on logs collected in real time with regard to the online behavior of a user who accesses an online site, the purchase intention of the user and the item of interest may be detected based on the behavior data, keyword ranking information related to the user may be extracted in consideration of the similarity between a keyword vector corresponding to the item of interest and item models created based on multiple items registered in the online site, and a user intention profile for the user may be created based on at least one of the item of interest, the keyword ranking information, and a purchase probability included in the purchase intention.

Abstract: Disclosed herein are a method for providing marketing management data for optimization of distribution and logistics and an apparatus for the same. The method and apparatus detect, in real time, respective purchase intentions of multiple users who access an online site, generate demand forecast data, in which items and regions are taken into consideration, based on respective pieces of user information and the purchase intentions of the multiple users, and generate and provide marketing management data for optimizing distribution and logistics of multiple items provided by the online site, based on the demand forecast data. Further, information that assists item sellers in managing inventory or in managing the supply and demand of products may be provided.

Abstract: Disclosed herein are a method for predicting a purchase probability based on a behavior sequence of a user and an apparatus for the same. The method and apparatus collect, in real time, logs for a user who accesses a shopping site, generate a Uniform Resource Identifier (URI) sequence corresponding to the online behavior of the user by arranging the logs in temporal sequence, and calculate a product purchase probability of the user by comparing the URI sequence with a purchase probability model corresponding to the shopping site. Further, the current purchase intention of a customer may be more accurately detected, and thus information about a product currently of interest to the customer may be provided.

Abstract: The present invention relates to the use of a plurality of dependency trees in tree-based statistical machine translation and proposes a dependency forest to effectively process the plurality of dependency trees. The present invention can improve a translation capability by generating a translation rule and a dependency language model by using the dependency forest and applying the generated translation rule and dependency language model when a source language text is converted to a target language text.

Abstract: The present disclosure relates to a syntax parsing apparatus based on syntax preprocessing and a method thereof. In specific, the present disclosure parses syntaxes that can be parsed by rules and patterns without ambiguity by syntax parsing preprocessing, draws all possible syntax parsing results by applying syntax rules based on a result of syntax parsing preprocessing in which ambiguity is partially resolved, and resolves structural ambiguity by applying a statistic syntax parsing model learned from a syntax tree attachment learning corpus so as to reduce ambiguity in rule-based syntax parsing and to resolve ambiguity by a statistics-based scheme so that parsing correctness and processing efficiency in a syntax parsing method can be enhanced.

Abstract: The present disclosure relates to a syntax parsing apparatus based on syntax preprocessing and a method thereof. In specific, the present disclosure parses syntaxes that can be parsed by rules and patterns without ambiguity by syntax parsing preprocessing, draws all possible syntax parsing results by applying syntax rules based on a result of syntax parsing preprocessing in which ambiguity is partially resolved, and resolves structural ambiguity by applying a statistic syntax parsing model learned from a syntax tree attachment learning corpus so as to reduce ambiguity in rule-based syntax parsing and to resolve ambiguity by a statistics-based scheme so that parsing correctness and processing efficiency in a syntax parsing method can be enhanced.

Abstract: The present disclosure relates to a syntax parsing apparatus based on syntax preprocessing and a method thereof. In specific, the present disclosure parses syntaxes that can be parsed by rules and patterns without ambiguity by syntax parsing preprocessing, draws all possible syntax parsing results by applying syntax rules based on a result of syntax parsing preprocessing in which ambiguity is partially resolved, and resolves structural ambiguity by applying a statistic syntax parsing model learned from a syntax tree attachment learning corpus so as to reduce ambiguity in rule-based syntax parsing and to resolve ambiguity by a statistics-based scheme so that parsing correctness and processing efficiency in a syntax parsing method can be enhanced.

Abstract: Disclosed herein are a system for content recommendation service, a content recommendation device and a method of operating the same. The system can recommend personalized content directly related with a recommendation target, irrespectively of whether the content consumption history of the recommendation target user is sufficient to analyze the purchase/use pattern or whether there are other users having similar purchase/user pattern with the recommendation target user. As a result, the recommendation reliability can be improved.

Abstract: The present disclosure relates to a syntax parsing apparatus based on syntax preprocessing and a method thereof. In specific, the present disclosure parses syntaxes that can be parsed by rules and patterns without ambiguity by syntax parsing preprocessing, draws all possible syntax parsing results by applying syntax rules based on a result of syntax parsing preprocessing in which ambiguity is partially resolved, and resolves structural ambiguity by applying a statistic syntax parsing model learned from a syntax tree attachment learning corpus so as to reduce ambiguity in rule-based syntax parsing and to resolve ambiguity by a statistics-based scheme so that parsing correctness and processing efficiency in a syntax parsing method can be enhanced.

Abstract: The present disclosure relates to an apparatus and a method for recognizing an idiomatic expression using phrase alignment of a bilingual parallel corpus, and more particularly, to an apparatus and a method for recognizing an idiomatic expression using phrase alignment of a parallel corpus which extract a candidate idiomatic expression using phrase alignment information of a bilingual parallel corpus and measure an idiomatic expression index for every extracted candidate idiomatic expression to recognize the candidate idiomatic expression as an idiomatic expression to resolve errors in measuring a translational entropy of a word and extracting a representative translated word of the word and improve the accuracy of the idiomatic expression recognition.

Abstract: An apparatus and a method for constructing a verb phrase translation pattern using a bilingual parallel corpus. Each of the apparatus or method recognizes a predicate and an argument using a syntax analysis result and a word alignment result of a source sentence from a plurality of bilingual parallel corpus, extracts a translation pattern candidate and an occurrence frequency using the recognized predicate and argument, and then generates a basic verb phrase translation pattern by verifying the translation pattern candidate, and generalizes the generated basic verb phrase translation pattern to generate a general verb phrase pattern so as to be applied to various language pairs and minimize an error in the verb phrase translation pattern and determine an appropriate generalization level using a co-occurrence frequency of a predicate and an argument of the verb phrase translation pattern and a translation probability of the predicate.

Abstract: Disclosed all an apparatus and a method for constructing a verb phrase translation pattern using a bilingual parallel corpus which recognizes a predicate and an argument using a syntax analysis result and a word alignment result of a source sentence from a plurality of bilingual parallel corpus, extracts a translation pattern candidate and an occurrence frequency using the recognized predicate and argument, and then generates a basic verb phrase translation pattern by verifying the translation pattern candidate, and generalizes the generated basic verb phrase translation pattern to generate a general verb phrase pattern so as to be applied to various language pairs and minimize an error in the verb phrase translation pattern and determine an appropriate generalization level using a co-occurrence frequency of a predicate and an argument of the verb phrase translation pattern and a translation probability of the predicate.

Abstract: Disclosed are a joint decoding apparatus and a joint decoding method that joins a tokenization process and a translation process. More particularly, the present disclosure can generate all available candidate tokens, reduce translation errors, and obtain an optimal translation result by jointly conducting a decoding by simultaneously conducting the tokenization process and the translation process for an input character sequence while decoding.

Abstract: The present invention relates to statistical machine translation, and provides a machine translation device and a machine translation method that acquire a creation probability for a target language from a single corpus while extracting respective conversion probabilities by extracting syntax conversion knowledge and word translation knowledge from a parallel corpus, model a weighted translation model by allowing each of the conversion knowledge and each of the probabilities to learn using a translation model learning device, and generate a target sentence through decoding processes of a syntax converter and a word translator by applying the translation model to a source sentence input in real time, thereby resolving disadvantages of the existing phrase-based SMT and syntax-based SMT and combining advantages thereof.

Abstract: The present invention relates to the use of a plurality of dependency trees in tree-based statistical machine translation and proposes a dependency forest to effectively process the plurality of dependency trees. The present invention can improve a translation capability by generating a translation rule and a dependency language model by using the dependency forest and applying the generated translation rule and dependency language model when a source language text is converted to a target language text.

Abstract: Disclosed are a joint decoding apparatus and a joint decoding method that joins a tokenization process and a translation process. More particularly, the present disclosure can generate all available candidate tokens, reduce translation errors, and obtain an optimal translation result by jointly conducting a decoding by simultaneously conducting the tokenization process and the translation process for an input character sequence while decoding.

Abstract: Disclosure relates to a statistical machine translation field, and more particularly to a method and a device for filtering a translation rule and generating a target word in a hierarchical phrase-based statistical machine translation. The method and device filters a translation rule using a relaxed-well-formed dependency structure and generates a target word by referring to a head word of a source word in a hierarchical phrase-based statistical machine translation. The disclosure improves a translation performance while reducing a number of translation rules, in comparison with a hierarchical phrase-based original translation rule table.