• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.338-343
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• 2020

This paper provides a semantic account of double nominative constructions in the framework of Autolexical Grammar, which views syntax, semantics, morphology, and other language components as modules generated simultaneously and independently. Some syntactocentric models in the past analyzed double nominatives as a result of possessor raising, ECM or incorporation. This paper provides a semantic explication of double nominatives through function-argument (F/A) structure of internal possession and external possession. The possessum used in double nominatives is a relational noun which takes a possessor as its argument in F/A structure. If the possessor directly combines with the relational noun, then internal possession is generated. If the possessor is a gap in F/A structure, then the argument which is coreferential with the gap combines later with the predicate, resulting in external possession, in which the possessor is in the nominative case. Unlike internal possession, the F/A structure of external possession structurally shows that the sentence is predicated of the possessor.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.199-231
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• 2010

This study tried to contrast the relation-based and the dimension-based explanations and to suggest its implications on the noun-noun conceptual combination. In experiment 1, we investigated whether the dimension-based approach and intra-conceptual explanation can explain both thematic relational and property interpretations of conceptual combinations based upon the intrinsic and extrinsic features of constituent concepts. We defined intrinsic(or extrinsic) concepts according to the degree of dependency on intrinsic(or extrinsic) features. Property interpretation was facilitated when modifiers were the intrinsic concepts. This result implies that processing of conceptual combination can be influenced by the structures and information of constituent concepts. In experiment 2, exocentricity of the concepts used in Gagne(2000) was examined to reanalyze her data according to the dimension-based approach. The exocentricity was higher when the concepts were combined by their relational connections. Results of experiment 1 and 2 suggest the possibility that both approaches can be integrated through the diversities of information involved during interpreting conceptual combination. Implications and future directions of this study were discussed.

• Language and Information
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• v.12 no.1
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• pp.27-65
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• 2008

This paper presents a set of methodologies for aligning hypernym-hyponym noun pairs between Korean and English, based on the EuroWordNet approach. Following the methods conducted in EuroWordNet, our approach makes extensive use of WordNet in four steps of the building process: 1) Monolingual dictionaries have been used to extract proper hypernym-hyponym noun pairs, 2) bilingual dictionary has converted the extracted pairs, 3) Word Net has been used as a backbone of alignment criteria, and 4) WordNet has been used to select the most similar pair among the candidates. The importance of this study lies not only on enriching semantic links between two languages, but also on integrating lexical resources based on a language specific and dependent structure. Our approaches are aimed at building an accurate and detailed lexical resource with proper measures rather than at fast development of generic one using NLP technique.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.76-85
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• 2012

Through opinion mining, we can analyze the degree of positive or negative sentiments that customers feel about important entities or attributes in online customer reviews. But, the limit of the opinion mining techniques is to provide only simple functions in analyzing the reviews. In this paper, we proposed novel techniques that can analyze the online customer reviews multi-dimensionally. The novel technique is to modify the existing OLAP techniques so that they can be applied to text data. The novel technique, that is, multi-dimensional analytic model consists of noun, adjective and document axes which are converted into four relational tables in relational database. The multi-dimensional analysis model would be new framework which can converge the existing opinion mining, information summarization and clustering algorithms. In this paper, we implemented the multi-dimensional analysis model and algorithms. we recognized that the system would enable us to analyze the online customer reviews more complexly.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.491-496
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• 2012

This study tried to analyze symbolism of the work from the title by looking into its linguistic meaning. The title not only exposes artist's thoughts but also speaks for the work subject. Also, it designates the world composed of characters in the work, and further it can be said as endowing overall meaning on the entire work by suggesting possibility of limitless meaning invention as well. As a result of reviewing the symbolism shown at the title after analyzing such points through linguistic contexts, the title named with Adam's language was used for just expressing the essence of characters in the work by transcending time and space, and the title meaning exposed relational aspects between characters and occurred accidents through the association process on 'signifiant' and 'signifie.' These relational aspects are expressed to mutual contraposition, but their relations finally show another one orientation too. In case of the title made by the arbitrary nature of language, a fact could be known that it was results of customs completely unrelated with the practical work and depended on the experience by any accident as being appeared from cultural background of the country where the work was produced. Also, the signification of language occurred in unique regulations and systems, and it was relevant to seeing things through concepts. The proper noun was disappeared, and the symbolism was given again from relational aspects accordingly. It was turn out that similarity between the work and title contained contents of entire work, and played a role of expressing greed in the narrative briefly.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.984-989
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• 2005

This study aims to identify grammatical relations (GRs) in Korean sentences. The key task is to find the GRs in sentences in terms of such GR categories as subject, object, and adverbial. To overcome this problem, we are fared with the many ambiguities. We propose a statistical model, which resolves the grammatical relational ambiguity first, and then finds correct noun phrases (NPs) arguments of given verb phrases (VP) by using the probabilities of the GRs given NPs and VPs in sentences. The proposed model uses the characteristics of the Korean language such as distance, no-crossing and case property. We attempt to estimate the probabilities of GR given an NP and a VP with Support Vector Machines (SVM) classifiers. Through an experiment with a tree and GR tagged corpus for training the model, we achieved an overall accuracy of $84.8\%,\;94.1\%,\;and\;84.8\%$ in identifying subject, object, and adverbial relations in sentences, respectively.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.74-82
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• 2022

The purpose of this paper is to provide a multi-modular account of double accusative constructions in Korean in the framework of Autolexical Grammar. The grammar views syntactic, semantic, and morphological structures of sentences as modules which are generated simultaneously and independently. Unlike syntactocentric theories, this paper analyzes semantic characteristics of double accusatives through function-argument (F/A) structure along with roles structure (RS) and information structure (IS). In F/A structure of double accusatives, the first accusative becomes an argument of a predicate, unlike the possessive, which is an argument of a relational noun. Furthermore, the first accusative of double accusatives takes the role of patient in RS, which allows it to become the subject of a passive sentence. On the other hand, the second accusative, which is originally the possessee, becomes a focal area in IS. Therefore, the purpose of double accusatives is twofold: one is to turn the possessor into an independent argument of a predicate which takes patient role, and the other is to turn the possessee into a focus. Such semantic characteristics of double accusatives can be expressed by means of multi-dimensional structures of F/A structure, RS, and IS of Autolexical Grammar, which allows an integrated account of the phenomenon.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.