摘要
[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 net- work 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.
作者
王福
毕强
张晗
Wang Fu;Bi Qiang;Zhang Han(School of Management,Jilin University,Changchun 130022)
出处
《图书情报工作》
CSSCI
北大核心
2018年第15期16-22,共7页
Library and Information Service
基金
国家自然科学基金项目“移动社交网络用户参与动机与网络互动机理研究-基于用户感知的调和作用”(项目编号:71501081)研究成果之一
关键词
移动图书馆
信息接受情境
情境感知计算
场景识别
人工神经网络
mobile libraries
information acceptance scenarios
context aware computing
scene recognition
artificial neural networks
