2024-08-04, 14:40–15:10 (Asia/Taipei), TR514
Searching through a vast collection of comics can be challenging. We often rely on matching titles, words, descriptions, publication years, character names, and publishers. But what about categorizing comics by genre or other intriguing criteria? In this session, we’ll explore Vector Index, a powerful index now use with relational databases and graph databases. We'll cover the basics of indexes, demystify Vector Index, and showcase its potential for more effective searches.
Join us to learn about Vector Index and its application in comic searches.
I'll explain how it works, its benefits, and how it can revolutionize your search experience.
Whether you're sorting comics by genre or exploring unique classifications, Vector Index offers exciting possibilities for unlocking insights from comic databases.
This session provides clear explanations suitable for beginners in databases.
Koji Annoura is a highly experienced full-stack developer with over 40 years of experience. He has been engaged in Agile software development since 2009 and played a pivotal role in establishing the "Neo4j Users Group Tokyo" in Japan. Moreover, in 2021, he founded the "Apache Hop User Group Japan" Koji has actively contributed to numerous companies and teams, guiding them through the Agile transformation process and facilitating the implementation of Agile and Scrum methodologies. An accomplished author, Koji has made significant contributions to "The Practical Guide to MacOS X Server" Additionally, he serves as a technical reviewer for "Graph Data Processing with Cypher