移動閱讀社交系統(tǒng)設(shè)計與實現(xiàn)
[Abstract]:Mobile smart devices allow people to access mobile Internet services anytime, anywhere. With the popularity of mobile smart devices, mobile application research is very hot. IOS and Android applications Store is growing at a rate of 30-40% per year, among which mobile reading applications are among the highest downloads among all mobile applications. However, the existing mobile reading applications are limited to provide e-book reading function, and do not fully play the role of mobile Internet: (1) users encounter problems in the process of reading, and can not quickly obtain authoritative explanations from experts in related fields. It is not efficient to obtain knowledge through search engine. (2) the variability of mobile reading environment makes it difficult for users to discuss each other's problems, and the existing mobile reading applications do not provide social platform for users. Recommendation based on reading questions can not be made; (3) the interface of electronic books is stereotyped, without simulating the effect of turning pages of real books, and the reading process of users is rather dull. In view of the above problems in mobile reading application, this paper designs a mobile reading social system, and obtains the following results: 1. A semantic annotation tool is implemented. Through this tool, domain experts can mark the knowledge points in electronic books. Electronic books with semantic tagging of knowledge points refine the granularity of knowledge acquisition from the whole article to knowledge points, which not only saves mobile Internet traffic, but also enables users to interact with each other quickly, thus accomplishing the "flash answer" function of electronic books. Experimental data show that using GPRS to access the mobile Internet and WiFi to access the Internet, the "flash" service is 10 times and 3 times faster than the search engine to view the entire article. A user recommendation algorithm based on knowledge point filtering is proposed. According to the historical information of browsing knowledge points in the course of reading books, the algorithm calculates the similarity of reading interest and the participation degree based on the interaction of knowledge points, and according to the results of user questionnaire, the two methods are weighted linearly. To recommend appropriate readers to help them solve the problems encountered in reading. The experimental results show that the proposed user recommendation algorithm based on Knowledge-Point filtering is in the range of 0.91-0.96 when the user behavior data is stable, and the ratio of the recommended results to the ideal results is close to 0.91-0.96. The average proximity ratio is as high as 0. 92, and the recommended effect is 3. 3%. The algorithm of simulating real book page turning is designed. Two full triangles are used to simulate the contents of the rolled page and the next page, and the vertex coordinates of each triangle are calculated. According to the triangle coordinate, the paper dynamically draws the page turning animation, and uses the Bessel curve as the smooth processing in the triangle edge, which makes the turning effect more close to the real situation. The function of simulating real book turning makes the reading process more interesting and provides users with a good reading environment and reading experience. 4. The Android terminal can read e-books, and the resource server can store the detailed information of the Android terminal and the information exchange between the Android terminal and the Openfire platform. The Android terminal presents the e-book for the user. The social network platform transmits the friends recommendation message and the social information between users, and displays the GPS geographical location information of the friends to the user, and promotes the online communication between users. The experimental results show that the mobile reading social system has high stability.
【學(xué)位授予單位】:湘潭大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:TP311.52
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