Ncsoft Corporation

Jung Sun Jang

Yeon Soo Lee

Hyung Jong Noh

Jun Yeop Lee

Sang Min Heo

Hyung Jun Kim

Disclosed are an apparatus and method for learning a narrative of a document, and an apparatus and method for generating a narrative of a document. According to an embodiment of the present disclosure, the narrative learning method includes the steps of receiving a plurality of documents, generating a topic database which includes one or more topics and words related to each of the one or more topics from the plurality of documents, splitting each of the plurality of documents into one or more segments including one or more sentences by using the topic database, grouping the segments split from each of the plurality of documents into one or more clusters, and generating a cluster label for each of the one or more clusters.

Apparatus and method for learning narrative of document, and apparatus and method for generating narrative of document

Disclosed are an apparatus and method for generating a natural language. According to an embodiment of the present disclosure, the method for generating the natural language includes receiving a plurality of pieces of data, generating a sentence ID sequence including one or more sentence IDs from the plurality of pieces of data, and generating a sentence corresponding to each of the sentence IDs included in the sentence ID sequence from the sentence ID sequence and the plurality of pieces of data.

Natural language generation of sentence sequences from textual data with paragraph generation model

Disclosed are an apparatus and method for verifying a sentence. According to one embodiment of the present disclosure, the method for verifying a sentence includes receiving a sentence automatically generated from a plurality of pieces of data, and the plurality of pieces of data; generating a first embedding vector for each word included in the sentence; generating a second embedding vector for each of the plurality of pieces of data; and generating a verification result value regarding the sentence by using a determination model including a first convolutional neural network for generating a feature vector from the first embedding vector and a second convolutional neural network for generating a feature vector from the second embedding vector.

Apparatus and method for verifying sentence

Disclosed are an apparatus and method for detecting a debatable document. According to an embodiment of the present disclosure, the method for detecting a debatable document includes the steps of receiving a document including one or more sentences; generating an embedding vector for each of words included in the document; and extracting features of the document from an embedding vector matrix including the embedding vectors for the words, and detecting debatability of the document from the extracted features through a detection model including a two-step convolutional neural network.

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Seongnam-si, South Korea

Jung Sun Jang