เพกาซัส: ระบบแนะนำเกมรายบุคคล
PEGASUS: Personalized Game Suggestion System
Abstract
ปัจจุบัน เกมเป็นสิ่งที่ได้รับความนิยมต่อบุคคลทุกเพศทุกวัย ส่งผลให้อุตสาหกรรมเกมเติบโตอย่างต่อเนื่องและเกมถูกพัฒนาขึ้นมาเป็นจำนวนมาก แต่อย่างไรก็ตาม เกมที่ถูกพัฒนาเหล่านั้นมีความคล้ายคลึงกันมาก ทำให้ผู้เล่นเกมตัดสินใจเลือกซื้อ
ได้ยาก บทความนี้จึงนำเสนอระบบแนะนำเกมที่เหมาะสมกับความชอบเฉพาะของผู้เล่นชื่อเพกาซัส เพกาซัสใช้การแนะนำโดยอ้างอิงเนื้อหาหรือวิเคราะห์จากประวัติของผู้เล่น โดยได้ทำการทดลองออกแบบมอดูลการแนะนำด้วย 2 วิธี ได้แก่ วิธีการหาค่าความคล้ายของโคโซน์ และวิธีการหาค่าน้ำหนักจากความถี่ของแท็กคำ ทั้งนี้เพื่อหาวิธีที่เหมาะสมที่สุดที่จะนำไปใช้ในระบบเพกาซัส ซึ่งการประเมินระบบทำโดยการเปรียบเทียบเกมที่ระบบแนะนำกับเกมที่ผู้เล่นเลือกเล่นจริง ผลการประเมินพบว่า การออกแบบมอดูลการแนะนำด้วยวิธีการคำนวณหาค่าน้ำหนักจากความถี่ของแท็กคำ มีค่าความถูกต้องสูงกว่าวิธีการหาค่าความคล้ายของโคโซน์
Currently, games are very popular among people of all ages and from all walks of life. Consequently, the game industry continues to grow, and new games are being developed in large numbers. However, those developed games are very similar. This makes it difficult for gamers to make purchasing decisions. This article, therefore, presents “Pegasus,” a personalized game recommendation system tailored to the specific preferences of players. The Pegasus function is on the basis of content-based recommendations or analysis of a player's game history. The experimental design of the recommendation module was carried out using two methods, i.e. the cosine similarity method and a word tag frequency weighting method. The most suitable method will be used in the Pegasus. The Pegasus system is evaluated by comparing the games recommended by the system with the games the players choose to play. The evaluation results reveal that the recommendation of the word tag frequency weighting method has higher accuracy than the cosine similarity method.
Keywords
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DOI: 10.14416/j.kmutnb.2023.07.008
ISSN: 2985-2145
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