The Design And Implementation Of Mobile Reading Social System

People can get mobile Internet services using mobile smart device any time anywhere.With the popularity of mobile smart devices, the research on mobile application is very hot.For example, the application stores of iOS and Android increase by30-40%per year,while the mobile reading applications’ download is among the best in all kinds ofapplications. However, the existing mobile reading applications have only e-book readingfunction, not fully play the role of the mobile Internet:(1) Users can’t get the authoritativeinterpretation of relevant experts when encountering an issue in reading. Usually, we mustbrowse documents to learn knowledge through a search engine, so that the efficiency ofknowledge acquisition appears low relatively.(2) Users discuss issues with each othervery hard because of the variability of mobile reading environment. Existing mobilereading application does not support social service, nor provide recommends based onreading.(3) The interface of e-book is monotony and the effect of flipping page is poor,both make user’s experience quite boring. Aimed at the above problems, we design amobile reading social system and do the following works:1. Implemented the semantic annotation tool. With this tool, expert can mark theknowledge points in an e-book. The e-books with knowledge semantic annotation makethe granularity of knowledge acquisition from the entire article to knowledge point. Itsaves the mobile Internet traffic and enables users to interact with knowledge quickly.Thereby the function of "quick-answer" for e-books is completed. Experimental data showthat compared to the communication speed of view an entire article using search engines,the speed of "quick-answer" service improve10X and3X using GPRS and WiFi accessmobile Internet respectively.2. A user recommend algorithm based on knowledge points filtering is proposed. Thealgorithm is based on the history information of browsing knowledge points during userread books. Then the similarity of reading interest and the participation based onknowledge points interaction between users are calculated. According to results of users’survey, the linear weighted for both can be done easily. Then a suitable reading answeringuser is recommended to target users to help them solve difficult problems encountered inreading. The experimental results show that the recommended results are very close to theideal results using the user recommend algorithm based on filtering knowledge point we proposed after the behavior data of users is stable. The ratio is between91%and96%withan average of up to92%. Totally, we achieve good recommended results.3. An algorithm for simulating turn pages of the real book is designed. The rolled partduring page turning and reveal part of next page are simulated by two congruent triangles.Then the coordinates of the vertices of each triangle are calculated. The animation of pageturning is drawn dynamically according to the coordinates of the triangle. It makes flipeffect more close to the real scene through smoothing the edge of triangle with Beziercurves. The function of simulating real page turning makes it more interesting whenreading to provide users with a nice reading environment and reading experience.4. The functions of reading e-book on Android devices, storing knowledge points and theirinformation into resource servers, and information interactive between Android devicesand Openfire platform are all realized. Android devices provide user e-books readingfunction. Social network system can transfer friends’ recommendation information andsocial information among users. It can also show the GPS of friends which facilitatescommunication among users online. Experimental tests verified the mobile reading systemhas a high social stability.