{"title":"Similarity-based ranking of videos from fixed-size one-dimensional video signature","authors":"Hugo Mendes, Paulo Seixas","doi":"10.1007/s10791-024-09459-0","DOIUrl":null,"url":null,"abstract":"<p>The amount of information is multiplying, one of the popular and widely used formats is short videos. Therefore, maintaining the copyright protection of this information, preventing it from being disclosed without authorization, is a challenge. This work presents a way to rank a set of short videos based on a video profile similarity metric, finding a set of reference videos, using a self-supervised method, without the need for human tagging. The self-supervised method uses a search based on a Genetic Algorithm, of a subgroup of the most similar videos. Similarities are calculated using the SMAPE metric on video signatures vectors, generated with a fixed size, using Structural Tensor, maximum sub matrix and T-SNE.</p>","PeriodicalId":54352,"journal":{"name":"Information Retrieval Journal","volume":"40 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Retrieval Journal","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10791-024-09459-0","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The amount of information is multiplying, one of the popular and widely used formats is short videos. Therefore, maintaining the copyright protection of this information, preventing it from being disclosed without authorization, is a challenge. This work presents a way to rank a set of short videos based on a video profile similarity metric, finding a set of reference videos, using a self-supervised method, without the need for human tagging. The self-supervised method uses a search based on a Genetic Algorithm, of a subgroup of the most similar videos. Similarities are calculated using the SMAPE metric on video signatures vectors, generated with a fixed size, using Structural Tensor, maximum sub matrix and T-SNE.
期刊介绍：
The journal provides an international forum for the publication of theory, algorithms, analysis and experiments across the broad area of information retrieval. Topics of interest include search, indexing, analysis, and evaluation for applications such as the web, social and streaming media, recommender systems, and text archives. This includes research on human factors in search, bridging artificial intelligence and information retrieval, and domain-specific search applications.
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