摘要
[目的/意义]为有效解决基于用户信息需求期望、信息搜索习惯和信息接受偏好的"场景—用户—情境"的适配问题。需要对移动图书馆场景化无序的信息接受情境进行聚合,形成适配用户信息接受期望的信息接受情境。[方法/过程]以移动图书馆场景化信息接受情境聚合为基础,以云舟知识服务空间为例,构建了移动图书馆信息接受情境聚合适配模型。[结果/结论]利用Hopefield的TSP神经网络算法对模型进行了仿真,对移动图书馆信息接受情境聚合适配效果进行评价。
[Purpose/significance] In order to effectively solve the adaptation issues of scenario,user,and scene in users' information needs expectation,information search habit and information acceptance preference,it is necessary to aggregate the disordering information acceptance contexts in scenario-based mobile library and form a information acceptance context that can adapt to users' information acceptance expectation. [Method/process] Based on mobile library's scenario-based information acceptance contexts aggregation,and taking Yun Zhou knowledge service space as an example,this paper constructs a mobile library information acceptance contexts aggregation adaptation model. [Result/conclusion] The TSP algorithm of Hopefield neural network is used to simulate the model and evaluate the adaptation effect of mobile library's information acceptance contexts aggregation.
出处
《情报理论与实践》
CSSCI
北大核心
2018年第6期22-27,21,共7页
Information Studies:Theory & Application
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"的研究成果之一
项目编号:71501081
关键词
移动图书馆
信息接受情境
情境聚合
情境适配
mobile library
information acceptance context
context aggregation
context adaptation