{"title":"Outlines of a Graph-Tensor Based Adaptive Associative Search Model for Internet of Digital Reality Applications","authors":"Tarek Setti, Á. Csapó","doi":"10.1109/IoD55468.2022.9987234","DOIUrl":null,"url":null,"abstract":"Internet of Digital Reality (IoD) is a technological vision that promises to radically transform existing digital ecosystems in a way that enables users to access all the content and capabilities - whether physical or digital - relevant to a goal-driven purpose in a highly integrated single environment. In this paper, we focus on a specific challenge that we expect will be crucial in making advances in this field: namely, the challenge of developing an effective search method that is personalized, adaptive and associative. As a possible solution to this challenge, we propose a graph-tensor based information model that incorporates the history of search keywords and inferred associations between them across potentially multiple search dimensions. We provide a brief discussion on why we assume this model to have advantageous properties and provide a short use-case example to motivate further research.","PeriodicalId":376545,"journal":{"name":"2022 IEEE 1st International Conference on Internet of Digital Reality (IoD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 1st International Conference on Internet of Digital Reality (IoD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IoD55468.2022.9987234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Internet of Digital Reality (IoD) is a technological vision that promises to radically transform existing digital ecosystems in a way that enables users to access all the content and capabilities - whether physical or digital - relevant to a goal-driven purpose in a highly integrated single environment. In this paper, we focus on a specific challenge that we expect will be crucial in making advances in this field: namely, the challenge of developing an effective search method that is personalized, adaptive and associative. As a possible solution to this challenge, we propose a graph-tensor based information model that incorporates the history of search keywords and inferred associations between them across potentially multiple search dimensions. We provide a brief discussion on why we assume this model to have advantageous properties and provide a short use-case example to motivate further research.