Event Source Page Discovery via Policy-Based RL with Multi-task Neural Sequence Model

Chia Hui Chang, Yu Ching Liao, Ting Yeh

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

The problem of finding event announcement pages for any given website is called event source page discovery. In this paper, we show a policy-based deep reinforcement learning (RL) model for the event source page discovery agent. We use two stages to train our agent, pre-training and fine-tuning. In the pre-training phase, the model is trained with limited labeled data, where each episode has a fixed number of steps. In the fine-tuning phase, the agent is trained using unlabeled data and a reward system based on an event source page classifier. The agent learns whether to continue exploring or stop exploring through an adaptive threshold. The proposed agent achieves 74% precision with a 1.28 unit cost (the average number of clicks for each event source page) on the real word data set.

原文???core.languages.en_GB???
主出版物標題Web Information Systems Engineering – WISE 2022 - 23rd International Conference, Proceedings
編輯Richard Chbeir, Helen Huang, Fabrizio Silvestri, Yannis Manolopoulos, Yanchun Zhang, Yanchun Zhang
發行者Springer Science and Business Media Deutschland GmbH
頁面597-606
頁數10
ISBN(列印)9783031208904
DOIs
出版狀態已出版 - 2022
事件23rd International Conference on Web Information Systems Engineering, WISE 2021 - Biarritz, France
持續時間: 1 11月 20223 11月 2022

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13724 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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???event.eventtypes.event.conference???23rd International Conference on Web Information Systems Engineering, WISE 2021
國家/地區France
城市Biarritz
期間1/11/223/11/22

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