从微博中提取当地事件信息,用于行程规划

Wataru Yamada, D. Torii, Haruka Kikuchi, H. Inamura, Keiichi Ochiai, Ken Ohta
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引用次数: 3

摘要

本文描述了一种从微博服务Twitter中提取本地事件信息的方法。Twitter拥有无数用户发布的被称为tweet的短消息,涵盖各种主题,包括当地事件。我们的提议由三个步骤组成:1)使用支持向量机(SVM)方法从本地推文中提取与本地事件相关的推文;2)使用条件随机场(CRF)识别并提取推文中提到的本地事件的地点、名称和时间;3)使用地点和名称相似度聚合重复的本地事件信息。实验结果表明,该方法提取局部事件信息的精度高于传统方法。
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Extracting local event information from micro-blogs for trip planning
This paper describes a method to extract local event information from the micro-blog service Twitter. Twitter holds innumerable user-posted short messages called tweets that cover various topics including local events. Our proposal is composed of three steps: 1) extract tweets related to local events from local tweets by the Support Vector Machine (SVM) approach, 2) identify and extract the venues, names and times of local events mentioned in the tweets by applying Conditional Random Fields (CRF), 3) use the venues and similarity of names to aggregate duplicate local event information. We implement the proposed method and confirm that it extracts local event information with higher precision than the conventional methods.
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