N. Hoang-Xuan, Thang-Long Nguyen-Ho, C. Gurrin, Minh-Triet Tran
{"title":"Lifelog Discovery Assistant: Suggesting Prompts and Indexing Event Sequences for FIRST at LSC 2023","authors":"N. Hoang-Xuan, Thang-Long Nguyen-Ho, C. Gurrin, Minh-Triet Tran","doi":"10.1145/3592573.3593104","DOIUrl":null,"url":null,"abstract":"AI-assisted tools have become more prevalent than ever in the last few years. However, applying them to build a lifelog retrieval system is still non-trivial due to the disparity in interfaces and interactions. The Lifelog Search Challenge (LSC) aims to provide a testing ground where systems can be benchmarked in a highly competitive setting. In this paper, we present the fourth iteration of our participating system FIRST. For this year, we adopt generative models to equip the system with predictive ability rather than entirely relying on the user to input the query. We also index a sequence of images as an event for improved search speed. Finally, we demonstrate how the additional features can assist users in searching.","PeriodicalId":147486,"journal":{"name":"Proceedings of the 6th Annual ACM Lifelog Search Challenge","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th Annual ACM Lifelog Search Challenge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3592573.3593104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
AI-assisted tools have become more prevalent than ever in the last few years. However, applying them to build a lifelog retrieval system is still non-trivial due to the disparity in interfaces and interactions. The Lifelog Search Challenge (LSC) aims to provide a testing ground where systems can be benchmarked in a highly competitive setting. In this paper, we present the fourth iteration of our participating system FIRST. For this year, we adopt generative models to equip the system with predictive ability rather than entirely relying on the user to input the query. We also index a sequence of images as an event for improved search speed. Finally, we demonstrate how the additional features can assist users in searching.