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Academic Activities Transaction Extraction Based on Deep Belief Network
المؤلفون المشاركون
Zhang, Chengyuan
Wang, Xiangqian
Huang, Fang
Wan, Wencong
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-12-12
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers.
The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases.
The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision.
Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results.
However, because Deep Belief Network (DBN) model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction.
In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition.
In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields.
The results show that DBN model is more effective for the extraction of academic activities transaction information.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Xiangqian& Huang, Fang& Wan, Wencong& Zhang, Chengyuan. 2017. Academic Activities Transaction Extraction Based on Deep Belief Network. Advances in Multimedia،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1122349
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Xiangqian…[et al.]. Academic Activities Transaction Extraction Based on Deep Belief Network. Advances in Multimedia No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1122349
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Xiangqian& Huang, Fang& Wan, Wencong& Zhang, Chengyuan. Academic Activities Transaction Extraction Based on Deep Belief Network. Advances in Multimedia. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1122349
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1122349
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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