{"title":"Optimization of CTR Prediction in Recommendation with Rating-Time Decay","authors":"Andy Maulana Yusuf, A. Wibowo, Kemas Rahmat Saleh","doi":"10.1109/IAICT59002.2023.10205904","DOIUrl":"https://doi.org/10.1109/IAICT59002.2023.10205904","url":null,"abstract":"The Click-Through-Rate (CTR) prediction is a significant concern in the advertising industry, and this research aims to address the three open aspects of learning, feature, and bias that require attention in CTR. The research conducted a literature review and identified appropriate methods from previous research to tackle these aspects. The proposed model optimizes learning time, prevents over-fitting using an early stopping strategy, and handles bias recommendations using Rating-Time decay. Testing on user interest in new and unpopular items provides promising results, indicating that the user’s latest preferences align with the latest event for CTR. The study’s findings demonstrate that the proposed model resolves CTR and over-fitting issues and optimizes the learning aspect of CTR models.","PeriodicalId":339796,"journal":{"name":"2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123639727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael Cahyadi, M. Rafi, William Shan, J. Moniaga, Henry Lucky
{"title":"Accuracy and Fidelity Comparison of Luna and DALL-E 2 Diffusion-Based Image Generation Systems","authors":"Michael Cahyadi, M. Rafi, William Shan, J. Moniaga, Henry Lucky","doi":"10.1109/IAICT59002.2023.10205695","DOIUrl":"https://doi.org/10.1109/IAICT59002.2023.10205695","url":null,"abstract":"Image generation system is a system which generates images using prompts in form of text. Due to the large-scale use of automatic image generation, mainly diffusion-based systems, there needs to be an evaluation regarding the output quality generated. We conduct a qualitative analysis of the accuracy and fidelity of two image generation systems, DALL-E 2 and Luna, which differ greatly in their training datasets, algorithms, prompt handling, and output scaling. We employ a qualitative benchmarking methodology and find that DALL-E 2 outperforms Luna significantly in terms of both alignment and fidelity.","PeriodicalId":339796,"journal":{"name":"2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125866238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}