检索结果-南通市图书馆

2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Jiangling Yuan Hui Zhang Jiangfeng Ni State Key Laboratory of Software Development Environment Beihang University School of Computer Science 100191 Beijing China

＜正＞Personalized recommendation is an effective method to resolve the current problem of Internet information *** the recommendation systems,user modeling is a crucial *** the model can accurately describe the users’ interests directly determines the quality of the personalized *** present in most personalized service systems keywords models or user-item models are used to describe the users’ preferences,but vectors or matrixes used in these models do not contain semantic information,so it is difficult to accurately model the users’ interests and hobbies,and it is also hard to extend the users’ *** as a tool used to describe the domain knowledge is very powerful in conceptual describing and logical *** of the neighbor set of users or resources is also an important step in the recommendation,but at present three commonly used similarity algorithms have some shortcomings which lead the system sometimes difficulty to find similar users or *** paper presents a new ontology-based user modeling approach and an improved similarity *** experiments show that the user model presented in this paper can effectively describe the users’ personalized preferences,and we also prove that the improved similarity algorithm is better than other three commonly used similarity algorithms.

关键词： personalized recommendation ontology semantic reasoning user modeling similarity measure

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Agent modeling of user Preferences Based on Fuzzy Classified ANNs in Automated Negotiation

引用

Journal of Donghua University(English Edition) 2011年第1期28卷 45-48页

作者：顾铁军汤兵勇马溪骏李毅 Glorious Sun School of Business and Management Donghua University Institute of Computer Network System Hefei University of Technology Information Security System Testing Lab The Third Research Institute of Ministry of Public Security

In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user requirements to implement ecommerce activities like automated *** difficulty lies in the uncertainty of user preferences that include uncertain description and contents,non-linear and dynamic *** this paper,fuzzy language was used to describe the uncertainty and combine with multiple classified artificial neural networks(ANNs) for self-adaptive learning of user *** refinement learning results of various negotiation contracts' satisfaction degrees in the extent of fuzzy classification can be *** to unclassified computation,the experimental results illustrate that the learning ability and effectiveness of agents have been improved.

关键词： agent automated negotiation user modeling artificial neural network(ANN) fuzzy classification

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

ACTPred: Activity Prediction in Mobile Social Networks

引用

Tsinghua Science and Technology 2014年第3期19卷 265-274页

作者： Jibing Gong Jie Tang A.C.M. Fong School of Information Science and Engineering Yanshan University Department of Computer Science and Technology Tsinghua University University of Glasgow in Singapore

A current trend for online social networks is to turn *** social networks directly reflect our real social life,and therefore are an important source to analyze and understand the underlying dynamics of human behaviors （activities）.In this paper,we study the problem of activity prediction in mobile social *** present a series of observations in two real mobile social networks and then propose a method,ACTPred,based on a dynamic factor-graph model for modeling and predicting users＇ *** approximate algorithm based on mean fields is presented to efficiently learn the proposed *** deploy a real system to collect users＇ mobility behaviors and validate the proposed method on two collected mobile *** results show that the proposed ACTPred model can achieve better performance than baseline methods.

关键词： social prediction activity prediction user modeling social networks

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

数字图书馆中个性化主动服务系统的研究(英文)

数字图书馆中个性化主动服务系统的研究(英文)

引用

第十八届全国数据库学术会议

作者： Xing Chunxiao Zeng Chun Zhang Zhiqiang Zhou Lizhu (Department of Computer Science and Technology,Tsinghua University Beijing100084)

Information overload has become a serious problem for users of the digital library(DL) system. How to provide the right information to the right person within reasonable time duration is a very important goal for DL *** this paper,as a solution to this problem,we propose our research on building TH-PASS——a personalized active service system that is able to provide the users personalized filtering and notification service based on user modeling and user pattern learning/*** making use of relevance measure of multiple features:query keywords,term and citation vectors,user action parameters,the system’s performance is *** framework of TH-PASS is proposed, and the user model and profile learning are studied.

关键词： Digital library user modeling Profile Filtering user pattern discovery

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

搜索引擎中一种基于PLSA的用户模型

搜索引擎中一种基于PLSA的用户模型

引用

第二十三届中国数据库学术会议

作者：于芳王大玲于戈白旭辉东北大学信息科学与工程学院

1前言当前搜索引擎使用的基于关键词的搜索,忽略了用户的差异和用户动机。新一代的搜索引擎应该具有互动式搜索等特点,更需要对用户提供个性化

关键词： Search engine user modeling Requirement Behavior Feedback

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：