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Aktivní učení pro klasifikaci
dc.contributor.advisorVomlelová, Marta
dc.creatorBorchers, Mitchell
dc.date.accessioned2023-07-24T12:24:56Z
dc.date.available2023-07-24T12:24:56Z
dc.date.issued2023
dc.identifier.urihttp://hdl.handle.net/20.500.11956/181873
dc.description.abstractData and the collection and analysis of data plays an important role in everyday life even though it often goes unseen. In our case, our partner is using data to classify websites into different categories. We used active learning and other machine learning methods to help classify websites into these categories and to explore the data collection and classification process. We scraped text data from websites, translated the data to English, and then worked with machine learning tools to understand the data and classify it. We found that the xPAL active learning strategy and linear support vector classifiers seemed to perform best with our data. 1en_US
dc.languageEnglishcs_CZ
dc.language.isoen_US
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.subjectActive learning|Web mining|Classification|E-commerceen_US
dc.subjectaktivní učení|klasifikace|e-komercecs_CZ
dc.titleActive learning in E-Commerce Merchant Classification using Website Informationen_US
dc.typediplomová prácecs_CZ
dcterms.created2023
dcterms.dateAccepted2023-06-12
dc.description.departmentKatedra teoretické informatiky a matematické logikycs_CZ
dc.description.departmentDepartment of Theoretical Computer Science and Mathematical Logicen_US
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.identifier.repId247770
dc.title.translatedAktivní učení pro klasifikacics_CZ
dc.contributor.refereePilát, Martin
thesis.degree.nameMgr.
thesis.degree.levelnavazující magisterskécs_CZ
thesis.degree.disciplineComputer Science - Artificial Intelligencecs_CZ
thesis.degree.disciplineComputer Science - Artificial Intelligenceen_US
thesis.degree.programComputer Science - Artificial Intelligencecs_CZ
thesis.degree.programComputer Science - Artificial Intelligenceen_US
uk.thesis.typediplomová prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Katedra teoretické informatiky a matematické logikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Department of Theoretical Computer Science and Mathematical Logicen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csComputer Science - Artificial Intelligencecs_CZ
uk.degree-discipline.enComputer Science - Artificial Intelligenceen_US
uk.degree-program.csComputer Science - Artificial Intelligencecs_CZ
uk.degree-program.enComputer Science - Artificial Intelligenceen_US
thesis.grade.csVelmi dobřecs_CZ
thesis.grade.enVery gooden_US
uk.abstract.enData and the collection and analysis of data plays an important role in everyday life even though it often goes unseen. In our case, our partner is using data to classify websites into different categories. We used active learning and other machine learning methods to help classify websites into these categories and to explore the data collection and classification process. We scraped text data from websites, translated the data to English, and then worked with machine learning tools to understand the data and classify it. We found that the xPAL active learning strategy and linear support vector classifiers seemed to perform best with our data. 1en_US
uk.file-availabilityV
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra teoretické informatiky a matematické logikycs_CZ
thesis.grade.code2
uk.publication-placePrahacs_CZ
uk.thesis.defenceStatusO


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