PMF Model for Mining User Relations

Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to appl...

全面介紹

Saved in:
書目詳細資料
Main Authors: QIU, Minghui, YANG, Liu, JIANG, Jing
格式: text
出版: Institutional Knowledge at Singapore Management University 2013
主題:
在線閱讀:https://ink.library.smu.edu.sg/researchdata/10
https://github.com/yangliuy/NLPForumPostOTE
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. This package implements the construction of opinion matrices which are the input of PMF model. The main features include aspect identification, opinion expression identification and opinion relation extraction based on dependency path rules. More details of our methods for aspect identification, opinion identification and opinion relation extraction are described in the related paper http://aclweb.org/anthology/N13-1041.