[目的/意义]为克服普适计算环境对移动图书馆信息接受情境自身来源的多样性和异构性的感知和计算能力不足，以实现用户信息接受的畅体验。[方法/过程]以情境感知理论为基础，采用Hopfield神经网络算法取代情境本体构建和推理，构建移动图书馆场景识别机理模型。[结果/结论]该模型简化移动图书馆场景化情境配置的复杂度，场景识别的正确率可达73%。
[Purpose/significance] The paper aims to overcome the lack of perceived and computing ability for the diversity and heterogeneity of the mobile library information acceptance context in the pervasive computing environment, and achieve user's flow experience. [Method/process] Based on the context awareness theory, the Hopfield neural network algorithm is used to replace ontology construction and reasoning, and the mobile library scene recognition mechanism model is constructed. [Result/conclusion] This model simplifies the complexity of scene scenario configuration in mobile library. The accuracy rate of mobile library scene recognition can be adjusted by the refine threshold to meet the users' scene information acceptance expectation.
[1] WEISER M. The computer for the 21st century:specialized elements of hardware and software, connected by wires, radio waves and infrared, will be so ubiquitous that no one will notice their presence[J]. Readings in human-computer interaction, 1995, 1(1):933-940.
[2] CHEN H, FININ T, JOSHI A. An ontology for context-aware pervasive computing environments[J]. Knowledge engineering review, 2005, 18(3):197-207.
[3] 毕达天,晁亚男. 数字图书馆信息接受情境多维建构[J].情报理论与实践,2015(9):14-19.
[4] 张晓东.新媒体时代的知识传播要素及其模式研究[J].华中师范大学研究生学报,2013,20(4):106-111.
[5] HONG D, HIU D K W, SHEN V Y. Requirements elicitation for the design of context-aware applications in a ubiquitous environment[C]//International conference on electronic commerce. New York:ACM, 2005:590-596.
[6] 徐步刊,周兴社,梁韵基,等.一种场景驱动的情境感知计算框架[J].计算机科学,2012(3):216-221.
[7] LEMLOUMA T, LAYAIDA N. Context-aware adaptation for mobile devices[C]//IEEE international conference on mobile data management. Piscataway:IEEE Computer Society, 2004:106.
[8] BOTTA A, LAZZERINI B, MARCELLONI F, et al. Context adaptation of fuzzy systems through a muti-objective evolutionary approach based on a novel interpret ability index[J].Soft computing,2009, 13(5):437-449.
[9] LEI Z, GEORGANAS N D. Context-based media adaptation in pervasive computing[C]//Conference on Electrical and Computer Engineering. Piscataway:IEEE, 2001:913-918.
[10] HÖPKEN W, FUCHSM, ZANKER M, et al. Context-based adaptation of mobile applications in tourism[J]. Information technology & tourism, 2010, 12(2):175-195.
[11] ZOLKEPLI I A, KAMARULZAMAN Y. Social media adoption:the role of media needs and innovation characteristics[J]. Computers in human behavior, 2015, 43:189-209.
[12] 谭天,张子俊.我国社交媒体的现状、发展与趋势[J].编辑之友,2017(1):20-25.
[13] DEXTER J E, MATSUO R R, MORGAN B C. Spaghetti stickiness:some factors influencing stickiness and relationship to other cooking quality characteristics[J]. Journal of food science, 2010, 48(5):1545-1551.
[14] 赵一鸣,马费成.大数据环境对信息组织的影响[J].图书情报知识,2017(1):4-10.
[15] 袁红.社会化媒体环境下用户信息浏览策略的效率评价研究[J].情报理论与实践,2017(4):89-94.
[16] 曾子明,宋扬扬.面向读者的智慧图书馆嵌入式知识服务探析[J].图书馆,2017(3):84-89,100.
[17] 周玲元,段隆振.基于SOA的图书馆情境感知中间件架构研究[J].图书馆理论与实践,2016(2):61-64.
[18] 沈旺,马一鸣,李贺.基于情境感知的用户推荐系统研究综述[J].图书情报工作,2015,59(21):128-138.
[19] 李明理.新媒体时代的图书馆场景构建策略[J].图书情报工作,2016,60(6):46-53.
[20] 饶浩,文海宁,林育曼,等.改进的支持向量机在微博热点话题预测中的应用[J].现代情报,2017,37(3):46-51.
[21] 莫同,李伟平,吴中海,等.一种情境感知服务系统框架[J].计算机学报,2010,33(11):2084-2092.
[22] 仲伟汉,黄晞,张萧.一种设计离散型Hopfield神经网络权值的新方法[J].福建师范大学学报(自然科学版),2012,28(3):38-42.
[23] 马卓.数字图书馆微服务情境交互功能评估研究[D].长春:吉林大学,2017.
[24] 曾子明,陈贝贝.移动环境下基于情境感知的个性化阅读推荐研究[J].情报理论与实践,2015,38(12):31-36.
[25] 杨旸,林辉.基于离散Hopfield网络的上市公司财务困境预警研究[J].华东经济管理,2016,30(12):156-162.
[26] 王福,聂兰渤,郝喜凤.移动图书馆场景化信息接受畅融合研究[J].图书馆学研究,2018(2):77-83.
