出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In this paper, we describe an accurate and effective event detection method to detect events fromTwitter stream. It detects events using visual information as well as textual information to improvethe performance of the mining. It monitors Twitter stream to pick up tweets having texts and photosand stores them into database. Then it applies mining algorithm to detect the event. Firstly, it detectsevent based on text only by using the feature of the bag-of-words which is calculated using the termfrequency-inverse document frequency (TF-IDF) method. Secondly, it detects the event based onimage only by using visual features including histogram of oriented gradients (HOG) descriptors,grey-level co-occurrence matrix (GLCM), and color histogram. K nearest neighbours (Knn)classification is used in the detection. Finally, the final decision of the event detection is made basedon the reliabilities of text only detection and image only detection. The experiment result showed thatthe proposed method achieved high accuracy of 0.93, comparing with 0.89 with texts only, and 0.86with images only.
关键词：Imageprocessing; Multimedia; Data Mining; Event Detection
