Social Media Contact Information Extraction

Jian Qu, Nattakarn Phaphoom, Chinorot Wangtragulsang, D. Tancharoen
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Abstract

Extraction of personal information from unstructured data presents itself as a challenge, as location and context of the information are unpredictable. Especially in Thai language where there is no punctuation, capitalization or ending character that separate specific names from the rest of the sentence. We propose a system capable of automatically extracting named entity information from web site snippets, using Thai celebrities as the sample named entity group and then compare the system with popular celebrity websites. We have tested our method on Thai celebrities, and our method achieved better accuracy than MThai.
社交媒体联系信息提取
从非结构化数据中提取个人信息本身就是一个挑战,因为信息的位置和上下文是不可预测的。特别是在泰语中,没有标点符号、大写字母或结束字符将特定的名字与句子的其他部分分开。我们提出了一个能够从网站片段中自动提取命名实体信息的系统,以泰国名人为样本命名实体组,并将该系统与流行的名人网站进行比较。我们已经在泰国名人身上测试了我们的方法,我们的方法取得了比MThai更好的准确性。
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