自动化学报Issue(8)：1385-1393,9.DOI:10.16383/j.aas.2015.c140762
基于条件随机域模型的比较要素抽取研究
Extraction of Comparative Elements Using Conditional Random Fields
摘要
Abstract
With the rapid growth of the number of evaluative texts on the Web, sentiment analysis has attracted the attention of researchers all over the world. Extraction of comparative elements is one of the important tasks for sentiment analysis of comparative sentences. It is more meaningful that results of sentiment analysis combine with comparative elements. To improve the performance of comparative elements extraction, this paper proposes to introduce shallow parsing features, comparative word candidates and heuristic position information to conditional random fields (CRFs) for building a system model. The proposed method is not only free from introducing domain knowledge but also can effectively deal with sentences containing a few comparative relationships. Experiment results show that the performance of system is improved when introducing proposed features to the CRFs model. Meanwhile, compared with the best results of the 2012 Chinese opinion analysis evaluation, the F1-scores of the proposed method are higher than the maximum value.关键词
情感分析/比较要素抽取/浅层句法特征/比较词候选特征/启发式位置特征Key words
Sentiment analysis/comparative element extraction/shallow parsing feature/comparative word candidate/heuristic position feature引用本文复制引用
王巍,赵铁军,辛国栋,徐永东..基于条件随机域模型的比较要素抽取研究[J].自动化学报,2015,(8):1385-1393,9.基金项目
国家高技术研究发展计划(863计划)(2015AA015405),国家自然科学基金(61402134,61173073,61172099,61272384),国家国际科技合作专项(2014DFA11350)资助Supported by National High Technology Research and Devel-opment Program of China (863 Program)(2015AA015405), Na-tional Natural Science Foundation of China (61402134,61173073,61172099,61272384), and the Special Project of Interna-tional Science and Technology Cooperation of China (2014DFA11350) （863计划）
