Abstract:
A method and a server for extracting a topic and evaluating suitability of the extracted topic are disclosed. The topic extraction server includes a text preprocessing unit configured to extract noun from a document group and remove stopword from the extracted noun, a keyword extraction unit configured to calculate a weight of a noun and extracting a keyword representing the document group, a seed selection unit configured to calculate a weight of the extracted keyword and select a seed, an initial clustering unit configured to generate one cluster including the selected seed and a keyword shown by several times in a sentence including the selected seed, and a cluster combination unit configured to extract a topic group.
Abstract:
An apparatus and a method for predicting the pleasantness-unpleasantness index of words are disclosed. The disclosed apparatus includes: a computing unit configured to compute an emotion correlation between a word and one or more comparison word, compute emotion correlations between multiple reference words included in a reference word set and the one or more comparison word, compute multiple first absolute emotion similarity values between the word and the multiple reference words, and compute at least one second absolute emotion similarity value between a reference word and another reference word for all of the reference words included in the reference word set; and a prediction unit configured to predict the pleasantness-unpleasantness index of the word by using the multiple number of first absolute emotion similarity values, the at least one second absolute emotion similarity value, and a preset pleasantness-unpleasantness index of the multiple number of reference words.
Abstract:
Provided are a method and a system for predicting stock fluctuation prediction. A system for predicting stock fluctuation according to an embodiment of the present invention includes: a data collector and a preprocessor collecting news and KOSPI data and extracting words from the collected news through stopword removal and morphologic analysis, a sentiment dictionary constructor selecting sentiment words and calculating sentiment values of the sentiment words to construct a sentiment dictionary of a stock domain required for stock prediction, and a stock fluctuation prediction model constructor predicting fluctuation of a closing price of a next day to a closing price of a current day by combining a prediction model using the constructed sentiment dictionary and an ARIMA prediction model using the KOSPI data.
Abstract:
An apparatus and a method for predicting the pleasantness-unpleasantness index of words are disclosed. The disclosed apparatus includes: a computing unit configured to compute an emotion correlation between a word and one or more comparison word, compute emotion correlations between multiple reference words included in a reference word set and the one or more comparison word, compute multiple first absolute emotion similarity values between the word and the multiple reference words, and compute at least one second absolute emotion similarity value between a reference word and another reference word for all of the reference words included in the reference word set; and a prediction unit configured to predict the pleasantness-unpleasantness index of the word by using the multiple number of first absolute emotion similarity values, the at least one second absolute emotion similarity value, and a preset pleasantness-unpleasantness index of the multiple number of reference words.