Title :
Hot Topic Word Extraction of Tibetan Network Public Opinion
Author :
Yuan Sun ; Wenbin Guo
Author_Institution :
Sch. of Inf. Eng., Minzu Univ. of China, Beijing, China
Abstract :
This paper proposes a model to automatically extract Tibetan hot words. Through analysis the dynamic Tibetan webs 2012, we use a frequency-position weighing algorithm to compute weight of word. Meanwhile, we integrate with entropy, 3s criterion and variance to extract and track the Tibetan network hot words. Finally, the experimental results prove the model is effective.
Keywords :
entropy; information retrieval; social networking (online); statistical analysis; 3s criterion; Tibetan network public opinion; dynamic Tibetan webs 2012; entropy; frequency-position weighing algorithm; hot topic word extraction; variance; word weight; Computational modeling; Data mining; Educational institutions; Entropy; Information processing; Internet; Monitoring; Frequency-position weighing algorithm; Hot topic word; Tibetan Network Public Opinion;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2013 6th International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4799-2808-8
DOI :
10.1109/ICINIS.2013.71
