Eduardo Fermé , Marco Garapa , Maurício D.L. Reis , Yuri Almeida , Teresa Paulino , Mariana Rodrigues
{"title":"知识驱动的简介动态","authors":"Eduardo Fermé , Marco Garapa , Maurício D.L. Reis , Yuri Almeida , Teresa Paulino , Mariana Rodrigues","doi":"10.1016/j.artint.2024.104117","DOIUrl":null,"url":null,"abstract":"<div><p>In the last decades, user profiles have been used in several areas of information technology. In the literature, most research works, and systems focus on the creation of profiles (using Data Mining techniques based on user's navigation or interaction history). In general, the dynamics of profiles are made by means of a systematic recreation of the profiles, without using the previous profiles. In this paper we propose to formalize the creation, representation, and dynamics of profiles from a Knowledge-Driven perspective. We introduce and axiomatically characterize four operators for changing profiles using a belief change inspired approach.</p></div>","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":"331 ","pages":"Article 104117"},"PeriodicalIF":5.1000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0004370224000535/pdfft?md5=db488321dca5a05c84cb8b5f4f52cadf&pid=1-s2.0-S0004370224000535-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Knowledge-driven profile dynamics\",\"authors\":\"Eduardo Fermé , Marco Garapa , Maurício D.L. Reis , Yuri Almeida , Teresa Paulino , Mariana Rodrigues\",\"doi\":\"10.1016/j.artint.2024.104117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the last decades, user profiles have been used in several areas of information technology. In the literature, most research works, and systems focus on the creation of profiles (using Data Mining techniques based on user's navigation or interaction history). In general, the dynamics of profiles are made by means of a systematic recreation of the profiles, without using the previous profiles. In this paper we propose to formalize the creation, representation, and dynamics of profiles from a Knowledge-Driven perspective. We introduce and axiomatically characterize four operators for changing profiles using a belief change inspired approach.</p></div>\",\"PeriodicalId\":8434,\"journal\":{\"name\":\"Artificial Intelligence\",\"volume\":\"331 \",\"pages\":\"Article 104117\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0004370224000535/pdfft?md5=db488321dca5a05c84cb8b5f4f52cadf&pid=1-s2.0-S0004370224000535-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0004370224000535\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0004370224000535","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
In the last decades, user profiles have been used in several areas of information technology. In the literature, most research works, and systems focus on the creation of profiles (using Data Mining techniques based on user's navigation or interaction history). In general, the dynamics of profiles are made by means of a systematic recreation of the profiles, without using the previous profiles. In this paper we propose to formalize the creation, representation, and dynamics of profiles from a Knowledge-Driven perspective. We introduce and axiomatically characterize four operators for changing profiles using a belief change inspired approach.
期刊介绍:
The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.