Multifeature Interactive Fusion Model for Aspect-Based Sentiment Analysis
المؤلفون المشاركون
Zeng, Biqing
Han, Xuli
Zeng, Feng
Xu, Ruyang
Yang, Heng
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-12-19
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis technology.
In recent years, neural networks are widely used to extract features of aspects and contexts and proven to have a dramatic improvement in retrieving the sentiment feature from comments.
However, due to the increasing complexity of comment information, only considering sentence or word features, respectively, may cause the loss of key text information.
Besides, characters have more microscopic features, so the fusion of features between three different levels, such as sentences, words, and characters, should be taken into consideration for exploring their internal relationship among different granularities.
According to the above analysis, we propose a multifeature interactive fusion model for aspect-based sentiment analysis.
Firstly, the text is divided into two parts: contexts and aspects; then word embedding and character embedding are associated to further explore the potential features.
Secondly, to establish a close relationship between contexts and aspects, features fusion of both aspects and contexts are exploited in our model.
Moreover, we apply the attention mechanism to calculate fusion weight of features, so that the key features information plays a more significant role in the sentiment analysis.
Finally, we experimented on the three datasets of SemEval2014.
The results of experiment showed that our model has a better performance compared with the baseline models.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zeng, Biqing& Han, Xuli& Zeng, Feng& Xu, Ruyang& Yang, Heng. 2019. Multifeature Interactive Fusion Model for Aspect-Based Sentiment Analysis. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1194304
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zeng, Biqing…[et al.]. Multifeature Interactive Fusion Model for Aspect-Based Sentiment Analysis. Mathematical Problems in Engineering No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1194304
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zeng, Biqing& Han, Xuli& Zeng, Feng& Xu, Ruyang& Yang, Heng. Multifeature Interactive Fusion Model for Aspect-Based Sentiment Analysis. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1194304
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1194304
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر