With the development and popularization of the Internet and the rapid development of e-commerce platforms, resulting in a huge amount of commodity short text. Research on short text classification of commodities is of great significance to commodity circulation, consumer behavior research and advertising push. This paper takes the commodity short text data set as the object, and the Convolutional Neural Network (CNN) algorithm based on deep learning is used to construct the classification model. Experimental results show that CNN algorithm is better than traditional machine learning algorithms (Naive Bayes(NB), K Nearest Neighbor(KNN) and Support Vector Machine(SVM)) in commodity short text classification.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.