Intelligent System for Agent in Educational Game Using Dynamic Gram Similarity

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Citations (Scopus)

Abstract

Today, almost people like a game. A game can make people have fun when playing it. An exciting game must have many feature and menus especially artificial intelligent (AI) called enemy or agent. Agent in game can be build using any method to make smart and intellect. In educational game, smart agent must can choose and decide a right answer of question. In this research, we make an agent to answer English question using dynamic gram similarity. This method based on n-gram similarity method but it can check neighbor word on sentence. Result of this research indicates dynamic gram similarity has 66% which is more accurate answer than unigram, big ram and trigram similarity. The conclusion of this research is dynamic gram similarity can implement to agent in educational game and can answer grammar English question automatically.

Original languageEnglish
Title of host publicationProceedings - 2018 International Seminar on Application for Technology of Information and Communication
Subtitle of host publicationCreative Technology for Human Life, iSemantic 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages373-376
Number of pages4
ISBN (Electronic)9781538674864
DOIs
Publication statusPublished - 27 Nov 2018
Event3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018 - Semarang, Indonesia
Duration: 21 Sept 201822 Sept 2018

Publication series

NameProceedings - 2018 International Seminar on Application for Technology of Information and Communication: Creative Technology for Human Life, iSemantic 2018

Conference

Conference3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018
Country/TerritoryIndonesia
CitySemarang
Period21/09/1822/09/18

Keywords

  • Artificial Intelligent
  • Educational Game
  • Grammar English
  • Natural Language Processing
  • Text Similarity

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