Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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1 |
Material Type: Ata de Congresso
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A deep learning approach to predict individual internet voting use based on electoral register dataKovacs, Mate ; Serdült, UweIEEE 2022Texto completo disponível |
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2 |
Material Type: Ata de Congresso
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A BERT-based Approach to Alleviate Civic Tech Tools Overcrowding: A case study of Taiwan's JOIN e-petition systemWang, Ruihao ; Kovacs, Mate ; Kryssanov, Victor ; Serdült, Uwe2024Texto completo disponível |
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3 |
Material Type: Ata de Congresso
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A Multi-Label Classifier for Online Petition SystemsBuryakov, Daniil ; Kovacs, Mate ; Serdült, Uwe ; Kryssanov, Victor2024Texto completo disponível |
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4 |
Material Type: Ata de Congresso
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E-Participation Maturity Model Development based on the Cases of Germany, Japan and SwitzerlandSerdült, Uwe ; Hofmann, Gabriel ; Kovacs, Mate ; Sugimoto, Konatsu ; Watanabe, Yuuka2023Texto completo disponível |
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5 |
Material Type: Ata de Congresso
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Text Mining from Party Manifestos to Support the Design of Online Voting Advice ApplicationsBuryakov, Daniil ; Hino, Airo ; Kovacs, Mate ; Serdült, UweIEEE 2022Texto completo disponível |
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6 |
Material Type: Ata de Congresso
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Towards a Model of Online Petition Signing Dynamics on the Join Platform in TaiwanHuang, Hsin-Ying ; Kovacs, Mate ; Kryssanov, Victor ; Serdült, UweIEEE 2021Texto completo disponível |
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7 |
Material Type: Ata de Congresso
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A Machine Learning Approach to Analyze Fashion Styles from Large Collections of Online Customer ReviewsHananto, Valentinus Roby ; Kim, Soomin ; Kovacs, Mate ; Serdült, Uwe ; Kryssanov, VictorIEEE 2021Texto completo disponível |
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8 |
Material Type: Ata de Congresso
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Assessing Customer Needs Based On Online Reviews: A Topic Modeling ApproachJauhari, Thariq M ; Kim, Soomin ; Kovacs, Mate ; Serdült, Uwe ; Kryssanov, Viktor VCEUR-WS 2020Texto completo disponível |