Facebook Activity Event Extraction System

• Main Authors: Yuan-Hau Lin, 林圓皓
• Other Authors: Chia-Hui Chang
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/05477094084432808856

碩士 === 國立中央大學 === 資訊工程學系 === 104 === The popularity of social networks has made them a perfect medium for activity or advertising campaign promotion. Therefore, many people use Facebook pages to announce their advertising campaign. The purpose of this study is to extract activity events by constructing two named entity recognition models, namely activity name and location, via a Web NER model generation tool [1]. We enhance the tool by improving the tokenizer and alignment technique. In addition, we also use a large database of FB checkin places for location name recognition improvement. For entity relation extraction, we apply sequential pattern mining to find rules for start date, end date, and location coupling. We use 1,300 posts from Facebook to test the activity event extraction performance. The experimental results show 0.727, 0.694 F_1-score for activity name and location recognition; and 0.865, 0.72 F_1-score for start and end date extraction. Overall, the extraction performance for activity event extraction is 0.708.