کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410261 679132 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Active deep learning method for semi-supervised sentiment classification
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Active deep learning method for semi-supervised sentiment classification
چکیده انگلیسی

In natural language processing community, sentiment classification based on insufficient labeled data is a well-known challenging problem. In this paper, a novel semi-supervised learning algorithm called active deep network (ADN) is proposed to address this problem. First, we propose the semi-supervised learning framework of ADN. ADN is constructed by restricted Boltzmann machines (RBM) with unsupervised learning based on labeled reviews and abundant of unlabeled reviews. Then the constructed structure is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Second, in the semi-supervised learning framework, we apply active learning to identify reviews that should be labeled as training data, then using the selected labeled reviews and all unlabeled reviews to train ADN architecture. Moreover, we combine the information density with ADN, and propose information ADN (IADN) method, which can apply the information density of all unlabeled reviews in choosing the manual labeled reviews. Experiments on five sentiment classification datasets show that ADN and IADN outperform classical semi-supervised learning algorithms, and deep learning techniques applied for sentiment classification.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 120, 23 November 2013, Pages 536–546
نویسندگان
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