• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.459-476
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• 2008

The user needs to find the answer to your question is growing fast at the service using collective intelligent knowledge. In the previous researches, it was proven that the non-text information like view counting, referrer number, and number of answer is good in evaluating answers. There were also many works about evaluating answers using the various kinds of word dictionaries. In this work, we propose new method to evaluate answers to question effectively using user reputation that estimated by the social activity. We use a modified PageRank algorithm for estimating user reputation. We also use the similarity between question and answer. From the result of experiment in the Naver GisikiN corpus, we can see that the proposed method gives meaningful performance to complement the answer selection rate.

• Annual Conference on Human and Language Technology
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• 2002.10e
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• pp.184-188
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• 2002

본 논문에서는 단순히 주변에 위치하는 어휘들간의 문맥 공기 정보를 이용하는 방식과는 달리 국소 구문 관계 및 의미 공기 정보에 기반한 명사 의미 모호성 해소 방안을 제안한다. 기존의 WSD 방법은 구조 분석의 어려움으로 인하여 문장의 구문 관계를 충분히 고려하지 못하고 주변 어휘들과의 공기 관계로 그 의미를 파악하려 했다. 그러나 본 논문에서는 동사구의 논항 의미 관계뿐만 아니라 명사구내에서의 의미 관계도 고려한 국소 구문관계를 고려한 명사 의미 모호성 해소 방법을 제안한다. 이 때, 명사들의 의미는 자동번역 시스템의 목적에 맞게 공기(co-occurrence)하는 동사들에 따라 분류하였다. 그리고 한중 자동 번역 지식으로 사용되는 명사 의미 코드가 부착된 74,880 의미 격틀의 의미 공기정보를 이용하였으며 형태소 태깅된 말뭉치로부터 의미모호성이 발생하지 않게 의미 공기정보 및 명사구 의미 공기 정보를 자동으로 추출하였다. 실험 결과, 의미 모호성이 발생하는 명사들에 대해서 83.9%의 의미 모호성 해소 정확률을 보였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2595-2602
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• 2010

This paper introduces a mobile spam filtering system that considers the style of short text messages sent to mobile phones for detecting spam. The proposed system not only relies on the occurrence of content words as previously suggested but additionally leverages the style information to reduce critical cases in which legitimate messages containing spam words are mis-classified as spam. Moreover, the accuracy of spam classification is improved by normalizing the messages through the correction of word spacing and spelling errors. Experiment results using real world Korean text messages show that the proposed system is effective for Korean mobile spam filtering.

• Cross-Cultural Studies
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• v.33
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• pp.407-459
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• 2013

The paper pragmatically analyzes ellipsis in Russian and Polish colloquial and informal texts. The famous Polish writer Sławomir $Mro{\dot{z}}ek^{\prime}s$ "Exit to the South", written in Polish and Russian is used as a material for the analysis. Russian and Polish ellipsis in colloquial and informal texts have in common that the givenness and subjecthood of the elliptical co-referent play a crucial role. However, the ellipsis in two languages also has differences in many ways. Above all, in the Polish texts of colloquial and informal style, a theme is likely to be elliptical and the coreferential relation reaches to an extra-sentential antecedent, while the ellipsis in analysed Russian texts in most cases requires coordinate, subordinate or relative clauses, and the elliptical co-referent tends to have an intra-sentential antecedent. The ellipsis of the theme-subject is unmarked in Polish, where every verbal form has an ending denoting person. Unlike formal style which often allows explicit noun subject, Polish text of colloquial and informal style prefer null form of the subject in most cases. If Polish sentences have explicit theme-subjects, they disambiguate intervening and main themes, and indicate the contrast, the focus, the introduction of new narratives or the change of speaker's point of view. Sometimes direct speeches and deictic pronouns also need explicit theme-subjects in Polish sentences. On the other hand, the ellipsis of the theme-subject is marked in Russian even in colloquial and informal texts. The theme-subject can be deleted in Russian colloquial and informal texts, if the subject is a form of the first or the second person, or if the aspect and the tense of the antecedent sentence's verb are the same as those of the given sentence's verb and both the antecedent and the coreferential word have the nominative case.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.161-187
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• 2001

Starting with the meaning of the word quality, diverse concepts connoted by the term are examined. Instead of a bathtub curve, the desirable shape of a failure rate covering the entire life of a good product, which might be called hockey-stick line, is introduced. From the hockey-stick line and the definition of reliability, two measurements are extracted. The terms reliability, failure rate, product life, and durability are explained. From the customer's standpoint, the concept of product quality is classified in five factors, according to related technology: performance, reliability, conformance to specifications, customer perception, and fundamentals advantage. The correlation of the five factors for a first-class product is discussed, Since the market share of a company is determined as the competition result of its product value, defined as product quality and price, the market share increase is derived mathematically from the increment of product value. The market share increase, $\Delta$S, can be calculated from the present market share, S, and the oriented relative value increment of new product, R, to the current product in the same company for the same market target: $\Delta$S : $\Delta$(1-S). R/(1+S.R). Finally, the importance of separating warranty cost from the profit equation for the durables is explained.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.11-22
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• 1994

For the conventional systme based on word, it is very difficult to enlarge the number of vocabulary. To cope with this problem, we must use more fundamental units of speech. For example, syllables and phonemes are such units, Korean speech consists of initial consonants, middle vowels and final consonants and has characteristic that we can obtain syllables from speech easily. In this paper, we show a speech recognition system with the advantage of the syllable characteristics peculiar to the Korean speech. The algorithm of recognition system is the Time Delay Neural Network. To recognize many recognition units, system consists of initial consonants, middle vowels, and final consonants recognition neural network. At first, our system recognizes initial consonants, middle vowels and final consonants. Then using this results, system recognizes isolated words. Through experiments, we got 85.12% recognition rate for 2735 data of initial consonants, 86.95% recognition rate for 3110 data of middle vowels, and 90.58% recognition rate for 1615 data of final consonants. And we got 71.2% recognition rate for 250 data of isolated words.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.50-58
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• 2002

The information extraction is to delimit in advance, as part of the specification of the task, the semantic range of the output and to filter information from large volumes of texts. The most representative word of the document is composed of named entities and pronouns. Therefore, it is important to resolve coreference in order to extract the meaningful information in information extraction. Coreference resolution is to find name entities co-referencing real-world entities in the documents. Results of coreference resolution are used for name entity detection and template generation. This paper presents the heuristic-based approach for coreference resolution in Korean. We constructed the heuristics expanded gradually by using the corpus and derived the salience factors of antecedents as the importance measure in Korean. Our approach consists of antecedents selection and antecedents weighting. We used three kinds of salience factors that are used to weight each antecedent of the anaphor. The experiment result shows 80% precision.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.200.1-200.1
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• 2011

Underground air is a special energy source in Jeju and distributes lava cave, pyroclastic, open joint, and crushing zone. A possible area to utilize underground air is 85% of Jeju except to the nearby area of Sambang Mt. and 25m high coastal area from sea level. In Jeju, underground air is used for heating agricultural facilities such as greenhouse cultivated mangos, Hallbong and mandarin orange, pigsty, mushroom cultivation house, etc. and fertilizing natural $CO_2$ gas by suppling directly into agricultural facilities. But this heating method causes several problem because the underground air has over 90% relative humidity and is inadequate in heating for crops. Mangos are the most widely grown tropical fruit trees and have been cultivated since 1993 in Jeju. In Jeju, the cultivating area is about 20ha and amount of harvest is 275ton/year in 2010. In this study, the heat pump system using underground air as heat source was installed in mangos greenhouse which area is $495m^2$. The capacity of heat pump system and heat storage tank was 10RT, 5ton respectively and heating effect and heating performance of the system were analysed.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1305-1314
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• 2013

The existing tag based system deducts a retrieval result with low accuracy through the usage of a single tag matching by using tags tagged in contents. And the system doesn't provide effectively contents related information which the tags have, as the users place tags on contents without considering the priority and associative relation between tags. For a solve of above problems, this paper suggests a tag ranking system which extracts semantic similarity between tags and re-ranks the tags tagged in contents. In order to evaluate the performance of suggested system, this paper experiments and compares the ranking result of this paper's tag ranking system with the result of baseline method using tags tagged in images and frequency method adapting tag co-appearance frequency.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.19-26
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• 2018

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.