Korean Semantics 2021 KCI Impact Factor : 0.92

Korean | English

pISSN : 1226-7198 / eISSN : 2734-0171

Aims & Scope
The goal is to independently embrace the field of semantics, which has recently been actively researched globally, and to activate research on semantics, one of the key areas of Korean linguistics. In more detail, we want to comprehensively research and analyze lexical semantics, sentence aesthetics, speech aesthetics, cognitive aesthetics, and application semantics, and establish the direction of semantic research among researchers.
Kim Yoonshin

(Incheon University)

Citation Index
  • KCI IF(2yr) : 0.92
  • KCI IF(5yr) : 1.07
  • Centrality Index(3yr) : 1.847
  • Immediacy Index : 0.2857

Current Issue : 2022, Vol.77, No.

  • A Study on the Analysis and Improvement of the Defining Vocabulary of Korean Basic Dictionary -Focusing on the particles and endings-

    Kim hae won | 2022, 77() | pp.1~25 | number of Cited : 0
    The purpose of this study is to confirm whether the defining vocabulary of particles and endings in Korean Basic Dictionary is controlled and to propose an improvement so that can help Korean learners understanding. To this end, 357 definitions of particles and 757 definitions of endings were examined. In addition, it was compared and determined whether defining vocabulary used only once was properly used. As a result, 76 out of about 388 defining vocabulary of particles were used once. Among them, nouns accounted for the highest percentage with 37, followed by low-frequency vocabulary in the order of verbs, adjectives, adverbs, adnominals, connective endings, suffix, auxiliary particle. And 70 out of about 570 defining vocabulary of endings were used once. Also, nouns accounted for the highest percentage with 26, followed by low-frequency vocabulary in the order of verbs, adjectives, adverbs, auxiliary adjectives, connective endings, auxiliary verb, auxiliary particle, numeral. In this paper, in the case where it is determined that modification is necessary among low-frequency vocabulary, Standard Korean Language Dictionary, Korea University Korean Dictionary, Sejong Corpus were analyzed together and suggested improvement.
  • A study on new words, refined words and the direction of harmonious purification policy

    Kim Soon-ok | Shin Jung-Jin | 2022, 77() | pp.27~55 | number of Cited : 0
    This paper reviews the concept of purifying the Korean language and the direction of research it is headed in as discussed by researchers of language purification. It further examines the current state of refined words in terms of their maintenance and policy. Current line of research in language purification is limited in that it is restricted to generating refined terms. In order to overcome such limitation, the need to address the fundamental questions of ‘why’ and ‘how’ language purification should take place is highlighted. Successful language purification may be achieved provided the goals of purification as well as those put forth by the policies are clear and explicit. Six steps of language purification and how they should be implemented as a policy is suggested. Finally, the paper argues that language purification as a policy must be met with close inspection and evaluation, whose findings should be reincorporated into the process of creating refined words, allowing for a purification policy that is harmonious.
  • Encoding expectation and inference

    Hou, Bo-wen | Park, Jinho | 2022, 77() | pp.57~101 | number of Cited : 0
    When the speaker constructs a proposition and the corresponding sentence, she bases their structure on her or the hearer's expectation. Therefore, expectation is important in linguistics and cognitive science. When she experiences an event, this event can accord to expectation or not. This accordance or non-accordance can be encoded by linguistic expressions. ‘anina talulkka’ and ‘anin key anila’ are accordance markers, while ‘selma’ is a non-accordance marker. Various degree expressions can also be analyzed in terms of expectation. Expectation-related phenomena can be modeled by Bayesian inference