Wiki3C: Exploiting Wikipedia for Context-Aware Concept Categorization

Wiki3C: Exploiting Wikipedia for Context-Aware Concept Categorization - scientific work related to Wikipedia quality published in 2013, written by Peng Jiang, Huiman Hou, Lijiang Chen, Shimin Chen, Conglei Yao, Chengkai Li and Min Wang.

Overview

Wikipedia is an important human generated knowledge base containing over 21 million articles organized by millions of categories. In this paper, authors exploit Wikipedia for a new task of text mining: Context-aware Concept Categorization. In the task, authors focus on categorizing concepts according to their context. Authors exploit article link feature and category structure in Wikipedia, followed by introducing Wiki3C, an unsupervised and domain independent concept categorization approach based on context. In the approach, authors investigate two strategies to select and filter Wikipedia articles for the category representation. Besides, a probabilistic model is employed to compute the semantic relatedness between two concepts in Wikipedia. Experimental evaluation using manually labeled ground truth shows that proposed Wiki3C can achieve a noticeable improvement over the baselines without considering contextual information.