移動(dòng)閱讀社交系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)
發(fā)布時(shí)間：2018-08-05 16:50
【摘要】：移動(dòng)智能設(shè)備可以讓人們隨時(shí)隨地獲取移動(dòng)互聯(lián)網(wǎng)服務(wù)。隨著移動(dòng)智能設(shè)備的普及，移動(dòng)應(yīng)用研究非�；馃帷OS和Android的應(yīng)用Store以每年30-40%的速度增長，其中移動(dòng)閱讀應(yīng)用在所有移動(dòng)應(yīng)用中下載量名列前茅。但是，現(xiàn)有的移動(dòng)閱讀應(yīng)用僅僅局限于提供電子書閱讀功能，，沒有充分發(fā)揮移動(dòng)互聯(lián)網(wǎng)的作用：（1）用戶閱讀過程中遇到不懂的問題，無法快速獲得相關(guān)領(lǐng)域?qū)＜业臋?quán)威解釋，需要通過搜索引擎查詢知識相關(guān)文檔，獲取知識的效率不高；（2）移動(dòng)閱讀環(huán)境的多變性導(dǎo)致用戶互相討論問題成為難題，現(xiàn)有的移動(dòng)閱讀應(yīng)用沒有為用戶提供社交平臺，不能作出基于閱讀答疑的推薦；（3）電子書本的界面千篇一律，沒有模擬真實(shí)書本翻頁的效果，用戶閱讀過程相當(dāng)枯燥。針對移動(dòng)閱讀應(yīng)用中存在的上述問題，本文設(shè)計(jì)了移動(dòng)閱讀社交系統(tǒng)，取得了如下工作成果： 1.實(shí)現(xiàn)了語義標(biāo)注工具。通過該工具，領(lǐng)域?qū)＜铱梢詫﹄娮訒局械闹R點(diǎn)進(jìn)行標(biāo)注。帶知識點(diǎn)語義標(biāo)注的電子書本把知識獲取的粒度從整篇文章細(xì)化到知識點(diǎn)，既節(jié)省了移動(dòng)互聯(lián)網(wǎng)流量，又能使用戶快速進(jìn)行知識交互，從而完成電子書本的“閃答”功能。實(shí)驗(yàn)數(shù)據(jù)表明，在使用GPRS接入移動(dòng)互聯(lián)網(wǎng)和WiFi接入互聯(lián)網(wǎng)的情況下，“閃答”服務(wù)相比于利用搜索引擎查看整篇文章，分別提升了10倍和3倍的通信速度。 2.提出了一種基于知識點(diǎn)過濾的用戶推薦算法。該算法根據(jù)用戶閱讀書本過程中瀏覽知識點(diǎn)的歷史信息，計(jì)算出用戶間的閱讀興趣相似度和基于知識點(diǎn)交互的參與度；根據(jù)用戶調(diào)查表的結(jié)果對兩者線性加權(quán)，為目標(biāo)用戶推薦出合適的閱讀答疑用戶，幫助其解決閱讀中遇到的疑難問題。實(shí)驗(yàn)結(jié)果表明，本文設(shè)計(jì)的基于知識點(diǎn)過濾的用戶推薦算法在用戶行為數(shù)據(jù)穩(wěn)定后，推薦結(jié)果與理想結(jié)果接近比集中在0.91-0.96之間，平均接近比高達(dá)0.92，取得了較好的推薦效果。 3.設(shè)計(jì)了模擬真實(shí)書本翻頁算法。使用兩個(gè)全等三角形模擬翻頁中卷起的頁面和下一頁的內(nèi)容，并計(jì)算出每個(gè)三角形的頂點(diǎn)坐標(biāo)。根據(jù)三角形坐標(biāo)動(dòng)態(tài)繪制翻頁動(dòng)畫，并在三角形邊緣使用貝賽爾曲線作圓滑處理，使得翻頁效果更加逼近于真實(shí)情景。模擬真實(shí)書本翻頁的功能使得閱讀過程中的趣味性得以提高，為用戶提供良好的閱讀環(huán)境和閱讀體驗(yàn)。 4.實(shí)現(xiàn)了Android終端的電子書閱讀，資源服務(wù)器存儲知識點(diǎn)與知識點(diǎn)詳細(xì)信息，Android終端與Openfire平臺的消息交互等功能。Android終端為用戶呈現(xiàn)電子書。社交網(wǎng)絡(luò)平臺為用戶傳輸好友推薦消息和用戶間的社交消息，并向用戶展示好友的GPS地理位置信息，促進(jìn)用戶間的線上交流活動(dòng)。實(shí)驗(yàn)測試驗(yàn)證了移動(dòng)閱讀社交系統(tǒng)具有較高的穩(wěn)定性。
[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
本文編號：2166393
[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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