Automatic Construction and Global Optimization of a Multisentiment Lexicon.
Automatic Construction and Global Optimization of a Multisentiment Lexicon.
复制标题
多情感词典的自动构建和全局优化
DOI：
10.1155/2016/2093406
复制
发表时间：
2016
影响因子：
--
通讯作者：
Zhu P
中科院分区：
文献类型：
--
作者：
Yang X;Zhang Z;Zhang Z;Mo Y;Li L;Yu L;Zhu P
人工标注情感词汇需要耗费大量的人力和时间，而且情感强度难以准确量化。此外，对一个特定领域的过度强调极大地限制了领域情感词典的适用性（Wang et al.，2010年）。通过神经网络语言模型对大规模汉语语料进行统计训练，提出一种基于坐标偏移约束的多维情感词典自动构建方法。为了区分不同语境中表达积极或消极意义的词的情感极性，我们进一步提出了一个情感消歧算法，以增加我们的词典的灵活性。最后，我们提出了一个全局优化框架，提供了一个统一的方式来联合收割机几个人类注释的资源，学习我们的10维情感词典SentiRuc。实验结果表明，SentiRuc词典在类别标注测试、强度标注测试和情感分类任务中具有良好的上级性能。值得一提的是，在强度标签测试中，SentiRuc比第二名高出21%。
Manual annotation of sentiment lexicons costs too much labor and time, and it is also difficult to get accurate quantification of emotional intensity. Besides, the excessive emphasis on one specific field has greatly limited the applicability of domain sentiment lexicons (Wang et al., 2010). This paper implements statistical training for large-scale Chinese corpus through neural network language model and proposes an automatic method of constructing a multidimensional sentiment lexicon based on constraints of coordinate offset. In order to distinguish the sentiment polarities of those words which may express either positive or negative meanings in different contexts, we further present a sentiment disambiguation algorithm to increase the flexibility of our lexicon. Lastly, we present a global optimization framework that provides a unified way to combine several human-annotated resources for learning our 10-dimensional sentiment lexicon SentiRuc. Experiments show the superior performance of SentiRuc lexicon in category labeling test, intensity labeling test, and sentiment classification tasks. It is worth mentioning that, in intensity label test, SentiRuc outperforms the second place by 21 percent.
利用群众的智慧识别网络垃圾邮件
影响因子：
3.5
作者：
Liu, Yiqun;Chen, Fei;Ru, Liyun
通讯作者：
Ru, Liyun
影响因子：
5.6
作者：
Turney, PD;Littman, ML
通讯作者：
Littman, ML
DOI：
10.3991/ijet.v9i6.4110
发表时间：
2014-01-01
影响因子：
--
作者：
Colace, Francesco;De Santo, Massimo;Greco, Luca
通讯作者：
Greco, Luca