A study for categorizing relations between headword and aliases

Jiyoun Kim, Youngeun Koo, Yongjun Zhu

Research output: Contribution to journalArticlepeer-review


In this study, we propose a method of categorizing relations between a headword and its aliases using Korean Wikipedia data. We propose orthographically similar types and orthographically different types. Orthographically similar types are divided into 5 types: Word space, Pronunciation difference, Omission, Abbreviation, and Word order change while different types are also classified into 4 types: Foreign word, Acronym, Paraphrased expression and Call name. We show examples to verify the proposed method.

Original languageEnglish
Pages (from-to)691-692
Number of pages2
JournalProceedings of the Association for Information Science and Technology
Issue number1
Publication statusPublished - 2019 Jan

Bibliographical note

Publisher Copyright:
Author(s) retain copyright, but ASIS&T receives an exclusive publication license

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Library and Information Sciences


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