• Journal of Information Management
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• v.42 no.4
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• pp.137-154
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• 2011

A headword finding system is defined as an information retrieval system using a word gloss as a query. We use the gloss as a document in order to implement such a system. Generally the gloss is very short in length and then makes very difficult to find the most proper headword for a given query. To alleviate this problem, we expand the document using the concept of query expansion in information retrieval. In this paper, we use 2 document expansion methods : gloss expansion and similar word expansion. The former is the process of inserting glosses of words, which include in the document, into a seed document. The latter is also the process of inserting similar words into a seed document. We use a featureless clustering algorithm for getting the similar words. The performance (r-inclusion rate) amounts to almost 100% when the queries are word glosses and r is 16, and to 66.9% when the queries are written in person by users. Through several experiments, we have observed that the document expansions are very useful for the headword finding system. In the future, new measures including the r-inclusion rate of our proposed measure are required for performance evaluation of headword finding systems and new evaluation sets are also needed for objective assessment.

• (The)Study of the Eastern Classic
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• no.70
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• pp.157-183
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• 2018

Mokjae Lee Samhwan's "MaengHoEum" is the three poems of the Chinese quatrain of 5word 7poetry created according to the previous age. This poem is distinguished from the poem of the general "MaengHoHaeng" series because of it was created in the form of modern-style poetry of series, not a poetry of 5word or 7word or length phrase in a poem. The "MaengHoEum" of MokJae seems to have been built around 1801year when he was 73 years old. Therefore, his "MaengHoEum" can be called an allegory poetry or a society poetry and his poetry can be said that it was created under the criticism of the corrupt political power of the contemporary society, and the 'fierce tiger' which appeared in his poem refers to the factions of Noron Byek line which was the ruling power at that time. However, if you look at the "MaengHoEum" of MokJae, you will see a criticism of the real world, but the feeling is not intense or the description is not concrete. Although his poetry depicts the absurdity of the present reality, but he does not show positive criticism of reality or strong resistance. This characteristic, which can be seen in his poem "MaengHoEum", is the result of the study he pursued for the his life and is thought to be due to the weight of reality. The contradictions of the time of the Mokjae were never silent to him, but on the other hand he could not reveal his own struggle on the surface of the poem. Between his descendants, influenced by his actions, and the stinging gaze watching him, he had no choice but to end his feelings internally.

• Journal of The Korean Association For Science Education
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• v.41 no.2
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• pp.71-82
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• 2021

Learning efficiency can be maximized by careful matching of text features to expected reader features (i.e., linguistic and cognitive abilities, and background knowledge). The present study aims to explore whether this systematic principle is reflected in the development of science textbooks. The current study examined science textbook texts on 20 measures provided by Auto-Kohesion, a Korean language analysis tool. In addition to surface-level features (basic counts, word-related measures, syntactic complexity measures) which have been commonly used in previous text analysis studies, the present study included cohesion-related features as well (noun overlap ratios, connectives, pronouns). The main findings demonstrate that the surface measures (e.g., word and sentence length, word frequency) overall increased in complexity with grade levels, whereas the majority of the other measures, particularly cohesion-related measures, did not systematically vary across grade levels. The current results suggest that students of lower grades are expected to experience learning difficulties and lowered motivation due to the challenging texts. Textbooks are also not likely to be suitable for students of higher grades to develop the ability to process difficulty level texts required for higher education. The current study suggests that various text-related features including cohesion-related measures need to be carefully considered in the process of textbook development.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.63-79
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• 2022

Recently, various studies have been conducted on stock price prediction using machine learning and deep learning techniques. Among these studies, the latest studies have attempted to predict stock prices using limit order books, which contain buy and sell order information of stocks. However, most of the studies using limit order books consider only the trend of limit order books over the most recent period of a specified length, and few studies consider both the medium and short term trends of limit order books. Therefore, in this paper, we propose a deep learning-based prediction model that predicts stock price more accurately by considering both the medium and short term trends of limit order books. Moreover, the proposed model considers news headlines during the same period to reflect the qualitative status of the company in the stock price prediction. The proposed model extracts the features of changes in limit order books with CNNs and the features of news headlines using Word2vec, and combines these information to predict whether a particular company's stock will rise or fall the next day. We conducted experiments to predict the daily stock price fluctuations of five stocks (Amazon, Apple, Facebook, Google, Tesla) with the proposed model using the real NASDAQ limit order book data and news headline data, and the proposed model improved the accuracy by up to 17.66%p and the average by 14.47%p on average. In addition, we conducted a simulated investment with the proposed model and earned a minimum of $492.46 and a maximum of $2,840.93 depending on the stock for 21 business days.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.116-124
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• 2022

The purpose of this study is to examine the vertical and horizontal continuity between grades and publishers, respectively, by analyzing the readability of reading passages included in English textbooks for 5th and 6th grades of elementary school. In order to do so, a corpus was constructed with the reading passages contained in 10 textbooks, and the reading passages in each textbook were analyzed through Coh-Metrix. Also, it was examined whether there was a statistically significant difference between grades and publishers in readability through one-way ANOVA. The results are as follows. First, as a result of analyzing the difference in readability between publishers within the same grade, there was a statistically significant difference between fifth-grade textbooks in the L2 readability index. Second, as a result of analyzing the vertical continuity between grades within the publisher, the difficulty of textbook A was higher in grade 6 than grade 5 based on FRE and FKGL, which showed a statistically significant difference. On the other hand, when L2 readability was used as the standard, the difficulty of textbook B was lower in 6th grade than in 5th grade. This result seems to be because FRE and FKGL calculate readability based on sentence and word length, whereas L2 readability is based on content word overlap, word frequency, and syntactic similarity of sentences.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.83-105
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• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• Physical Therapy Rehabilitation Science
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• v.6 no.3
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• pp.134-139
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• 2017

Objective: Dual-task interference is defined as decrements in performance observed when people attempt to perform two tasks concurrently, such as a verbal task and walking. The purpose of this study was to investigate the changes of gait ability according to the dual task interference in chronic stroke survivors. Design: Cross-sectional study. Methods: Ten chronic stroke survivors (9 male, 1 female; mean age, 55.30 years; mini mental state examination, 19.60; onset duration, 56.90 months) recruited from the local community participated in this study. Gait ability (velocity, paretic side step, and stride time and length) under the single- and dual-task conditions at a self-selected comfortable walking speed was measured using the motion analysis system. In the dual task conditions, subjects performed three types of cognitive tasks (controlled oral word association test, auditory clock test, and counting backwards) while walking on the track. Results: For velocity, step and stride length, there was a significant decrease in the dual-task walking condition compared to the single walking condition (p<0.05). In particular, higher reduction of walking ability was observed when applying the counting backward task. Conclusions: Our results revealed that the addition of cognitive tasks while walking may lead to decrements of gait ability in stroke survivors. In particular, the difficulty level was the highest for the calculating task. We believe that these results provide basic information for improvements in gait ability and may be useful in gait training to prevent falls after a stroke incident.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.5
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• pp.451-460
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• 2004

The pilot bit pattern of W-CDMA system is used for the channel estimation and frame synchronization confirmation. This paper proposes the binary sequences for the frame synchronization for wideband code division multiple access (W-CDMA) system. We present the circuit for the generation of ideal frame synchronization property using the binary sequences called frame synchronization word(FSW). W-CDMA system uses compressed mode where up to 7 slots per one 10 msec frame are not transmitted to make measurements from another frequency without a full dual receiver terminal. It is shown that the proposed frame synchronization words also maintain the optimal frame synchronization property in the compressed mode by using the complementary mapping relationship of preferred pair. And we discuss the realization circuit for the generation of frame synchronization words by using the concept of preferred pairs, complementary mapping relationship, and maximal length sequence.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.515-524
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• 2012

This paper studied the statistics such as the total number of syllables, the kinds of syllables, the frequency of syllables, the number of eojeols(word phrases unique in Korean language), the kinds of eojeols, average length of eojeols, the frequency of eojeols and the parts of speech in four different Korean textbooks for 6th-grade students(6-1 Korean Reading, 6-1 Korean Speaking Listening Writing, 6-2 Korean Reading and 6-2 Korean Speaking Listening Writing). The results of the statistical survey are as follows: the number of Hangul syllables was 194,683; the kinds of syllables were 1,290; the average frequency of syllables was 150.9; the number of eojeol was 70,185; the kinds of eojeol were 22,647; the average frequency of eojeol was 3.1; the average length of eojeols was 2.8 syllables, the longest one consist of 10 syllables. In parts of speech, nouns are used more in the Korean Reading textbook, and verbs are used more in Korean Speaking Listening Writing.