Title :
A new modeling approach for Arabic opinion mining recognition
Author :
Cherif, Walid ; Madani, Abdellah ; Kissi, Mohamed
Author_Institution :
Lab. LIMA, Dept. of Comp. Sci., Fac. of Sci., Chouaib Doukkali Univ., El Jadida, Morocco
Abstract :
Over recent years, the world has experienced a huge growth in the volume of shared web texts. Its users generate daily a huge volume of comments and reviews related to different aspects of their lives. In general, opinion mining/sentiment analysis refers to the task of identifying positive and negative opinions, emotions and evaluations related to an article, news, products, services, etc [1]. Arabic Opinion mining is conducted in this study using a dataset consisting of 625 Arabic reviews and comments collected from Trip Advisor website. We introduce a new mathematical approach to recognize author´s opinion. As the weights computation is determining in the classification, we formulate first a linear program to maximize the distance between the considered classes, then we use these weights to calculate the label of each comment. A further post optimization is also treated to add other contributing descriptors in order to adjust the classification. The results which based on Support Vector Machines showed that the approach is the most influencing on opinion recognition.
Keywords :
Web sites; data mining; linear programming; natural language processing; support vector machines; Arabic opinion mining recognition; Trip Advisor Website; linear program; post optimization; sentiment analysis; shared Web texts; support vector machines; Accuracy; Computational modeling; Computer science; Data mining; Kernel; Sentiment analysis; Support vector machines; Arabic text; Automatic language processing; Information retrieval; Low-level light-Stemming; Opinion Mining; Support vector machines;
Conference_Titel :
Intelligent Systems and Computer Vision (ISCV), 2015
Conference_Location :
Fez
Print_ISBN :
978-1-4799-7510-5
DOI :
10.1109/ISACV.2015.7105541
