應用興趣點辨識技術從 Web 中挖掘新商家資訊

Kuo Hsin Hsu, Hsiu Min Chuang, Chien Lung Chou, Chia Hui Chang

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

This paper presents a system that could automatically extract new POIs from Web. First, we use special queries (e.g. Taipei+New Open) to find Web pages that might contain addresses for new stores. For web pages that contain addresses, we then apply store name recognition model to extract possible POIs. Finally, we train a model to find the most possible POI for the address found in the page. In this paper, we focus on POI name recognition and POI relation prediction. For POI recognition, we use store names from yellow pages as seed to prepare the training data via distant learning. Through entity selection and data processing, we obtain a model with 0.816 F1-measure as opposed to 0.432 F1-measure for a dictionary-based baseline. As for POI relation prediction, we compare three different strategies for negative example preparation. The best model could get 0.754 accuracy. We combine two POI recognition models with three classification models to test the overall performance. The best combination could extract 49 POIs every day with a single IP.

貢獻的翻譯標題Mining POIs from web via POI recognition and relation verification
原文繁體中文
主出版物標題Proceedings of the 29th Conference on Computational Linguistics and Speech Processing, ROCLING 2017
編輯Lun-Wei Ku, Yu Tsao, Chi-Chun Lee, Cheng-Zen Yang, Hung-Yi Lee, Richard T.-H. Tsai, Wen-Hsiang Lu, Shih-Hung Wu
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面53-67
頁數15
ISBN(電子)9789869576901
出版狀態已出版 - 1 11月 2017
事件29th Conference on Computational Linguistics and Speech Processing, ROCLING 2017 - Taipei, Taiwan
持續時間: 27 11月 201728 11月 2017

出版系列

名字Proceedings of the 29th Conference on Computational Linguistics and Speech Processing, ROCLING 2017

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???event.eventtypes.event.conference???29th Conference on Computational Linguistics and Speech Processing, ROCLING 2017
國家/地區Taiwan
城市Taipei
期間27/11/1728/11/17

Keywords

  • Address Recognition
  • POI Entity Recognition
  • POI Relation Prediction

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