网格资源访问的对等信任机制

针对传统网格信任模型中倾向于资源使用者抉择资源而忽略资源提供者的抉择这一现象,分析了信任关系具有的特性,建立了基于域的对等信任模型,并提出了一种更能充分发挥网格资源效率的对等信任机制.该机制认为网格的实体具有资源使用阈值和资源提供阈值,网格实体在进行资源的共享和协同时,交互双方在使用资源和提供资源方面都需要根据相应的阈值抉择匹配的信任度,并通过推荐信任链路建立对等信任关系.     

一种混合式P2P文件共享与检索模型

文件共享是当今对等网络应用的主要方面,本文通过对对等网络中信息共享规律的研究,提出一个基于用户兴趣相似性组成对等组的系统模型.在用户加入对等网时利用用户提供的共享文档信息将用户进行聚类,然后依据查询回馈信息动态调整网络的拓扑结构,尽可能保持对等组内及对等组间的语义相关性、偏爱一致性.为P2P信息检索研究提供了一些新的思路.     

一种基于内容相似度和推荐反馈的信任模型

在已有P2P模型的基础上提出了基于内容相似度和推荐反馈计算节点推荐值的对等网络信用模型IPBS(Integrated-partial based similarity Trust).该模型利用节点间的内容相似度来评价节点提供推荐服务的能力,根据每次交易的内容不同而改变节点间相似度值;同时依据节点交易历史时间和推荐反馈值自适应动态地调整节点的推荐值;实例表明,IPBS节点间推荐值,通过参考节点内容相似度、交易历史时间和推荐反馈3种机制,加强了模型的动态适应能力和搜索服务的效率.     

关联性动态加权的协同过滤推荐

利用传统的协同过滤（CF）算法进行推荐时,由于用户评分矩阵比较稀疏,直接得到的用户或者项目之间的相似度相对而言可信度就比较低。为了解决这个问题,在传统的协同过滤基础上,引入项目与项目之间的关联性,通过在项目的类别标签和二部图的方法之间构建动态权重因子来融合这两种关联,形成非对等关联性关系,并做出用户对项目的评分预测,从而解决评分矩阵过于稀疏的问题。研究结果表明,相比于传统方法中使用对等相似度关系以及固定权值的方法,通过动态权重融合关联性形成非对等的关系的方法,更贴合生活实际,并且有更好的推荐效果。     

多维关联规则推荐在商务站点中的应用

提出了一种多维关联规则推荐系统,为客户提供更加准确的个性化推荐。该系统利用了客户购物信息、注册信息数据和经过评估的客户消费能力信息,通过多维、多层次的关联规则挖掘生成推荐集。针对不同的客户提供不同的商品,从而改善了个性化推荐的效果。     

基于Bayes的对等网信任模型仿真与分析

针对对等网络环境中的信任关系的复杂性,动态性和不确定性以及传统的信任管理模型不能很好地适应对等网络,对基于Bayes概率统计的信任量化模型进行仿真与分析,在信任计算中,引入经验贝叶斯估计来计算直接信任值和推荐信任值,节点根据自身的情况进行权重分配,计算综合信任评价,最后提出了信任模型在对等网络中的实现方法。仿真结果显示,该模型具有很好的动态适应能力,可以有效地检测并隔离系统中的恶意节点,降低系统的服务失败率。     

对等网络中基于节点交互和推荐的信誉管理

提出与描述了对等网络中基于节点交互和推荐的信誉管理模型。该模型中的节点在进行文件下载时,可以直接参考推荐节点,而不是去参考其他大量数目的普通节点,节省大量的时间和减少通信代价。该模型认为节点的信誉能力是多方面的, 参考了概率论中的贝叶斯网络,把节点的性能指标按照贝叶斯网络组织起来,在节点交互和文件共享过程中对信誉分数进行更新。构建了信誉管理模型的测试环境,性能分析表明在进行大量的节点和文件上传与下载时,系统可以通过推荐节点使交互数目稳定增加;与普通的对等网络相比,成功的交互数目也稳定增加。     

标签模糊和冗余在标签推荐中的研究及应用

现有的Folksonomy标签推荐系统使用的推荐算法没有考虑标签模糊和冗余问题,影响了用户建模和对推荐系统评估的准确性,并且降低了系统的推荐质量,增加了用户选择喜好项目时的负担。通过对标签推荐系统的研究,将标签模糊和冗余应用到标签推荐算法当中,有助于提高系统的推荐质量,并且能提供更合理的评价方法。实验结果表明：经过标签模糊和冗余处理的标签推荐算法显著地提高了推荐系统的推荐质量。     

基于P2P网络的协同过滤推荐算法的研究与实现

协同过滤算法是当前电子商务推荐系统最有效的信息过滤技术之一。而传统协同过滤算法的最大弱点是可扩展性问题，随着用户数量以及商品项目的增加，计算复杂度的快速增长导致大规模电子商务系统的可扩展性问题．本文提出了一种基于P2P网络协同过滤推荐算法方法，采用对等计算的方法进行用户数据库的管理和评分预测工作，该系统充分利用P2P网络对等计算的优点，采用了多生成树的路由算法。实验数据表明了我们采用的基于P2P网络的分布式协同过滤方法较传统集中式算法有更好的可扩展性和预测准确性．     

基于智能推荐的网络购物系统的设计研究

目前越来越多的消费者通过网络购物系统购买商品,但是网络购物系统提供了大量的商品信息,这使得顾客无法快速地找到自己所需的商品。本文介绍了基于智能推荐的网络购物系统的设计方案,包括系统架构设计、系统功能的设计、智能推荐功能的设计、数据库的设计、系统界面的设计。基于智能推荐的购物系统能更好地了解用户的需求,以便能及时有效地为用户提供贴心的推荐服务。     

基于对等组的P2P安全通信机制

当前对P2P网络系统安全的研究大多着眼于构造信任和名誉模型,而对通信过程的安全问题研究较少。提出了一种基于对等组实现的P2P安全通信机制——P2PSCM。P2PSCM首先为通信节点构建安全对等组。组内节点相互通信时,先通过交换公私密钥和对称密钥建立节点间安全通信渠道;然后采用对称密钥加密传输数据;最后对接收数据进行身份确认与完整性验证,确保相互间安全通信。     

基于可信对等的分布式入侵检测通信框架设计

为了提高分布式入侵检测的实时性和安全性,提出了一种可信对等的分布式入侵检测通信框架的模型.该模型借鉴了P2P和代理技术,不同网络节点中的入侵检测代理是对等的,它们之间通过共享检测信息进行整体协防.该模型还借鉴了安全通信技术,在网络中建立了一个认证服务器,不在同一网络节点的任何两个网络进程的通信必须通过该认证服务器,提高了入侵检测自身的安全性.设计实现了一个原型系统,原型系统的实验结果表明了该模型的正确性和可行性.     

Improving essay peer grading accuracy in massive open online courses using personalized weights from student's engagement and performance

Most massive open online courses (MOOC) use simple schemes for aggregating peer grades, taking the mean or the median, or compute weights from information other than the instructor's opinion about the students' knowledge. To reduce the difference between the instructor and students' aggregated scores, some proposals compute specific weights to aggregate the peer grades. In this work, we analyse the use of students' engagement and performance measures to compute personalized weights and study the validity of the aggregated scores produced by these common functions, mean, and median, together with two others from the information retrieval field, the geometric and harmonic means. To test this procedure, we have analysed data from a MOOC about Philosophy. The course had 1,059 students registered, and 91 participated in a peer review process that consisted in writing an essay and rating three of their peers using a rubric. We compared the aggregation scores obtained using weighted and nonweighted versions of the functions. Our results show that the correlation between the aggregated scores and the instructor's grades can be improved in relation to peer grading, when using the median and weights are computed according to students' performance in chapter tests.     

Structuring the peer assessment process: a multilevel approach for the impact on product improvement and peer feedback quality

In order to optimize students' peer feedback processes, this study investigates how an instructional intervention in the peer assessment process can have a beneficial effect on students' performance in a wiki environment in first‐year higher education. The main aim was to study the effect of integrating a peer feedback template with a varying structuring degree. The present study involved three conditions: a no structure, a basic structure and an elaborate structure condition. Due to a clear hierarchical structure, in which over time (level 1), 168 students (level 2) are nested within 37 groups (level 3), multilevel analysis was performed to examine the effect of time, student and group level influences on students' peer feedback quality and product scores. The results revealed that both peer feedback quality and product scores increase significantly for all conditions over time, after multiple practice occasions. In addition, after several practice occasions, significant differences were found between the conditions in both peer feedback (elaborate higher than no structure) and product scores (elaborate and basic higher than no structure). Building on this, limitations, directions for future research and practical implications are presented.     

网格环境中基于对等代理的复制定位机制

针对目前网格环境中复制定位机制存在的问题，并综合考虑其中的优势，提出了一种基于对等代理的分布式复制定位机制，即通过对等代理组成分布式的虚拟全系统，实现全域网络里最大有效范围内的复制定位，比起传统的基于分级机制和分布式查询与索引机制的定位服务，在性能、安全、可靠性和有效性上都有很大的改善和提高。     

P2P网络中自适应节点选择策略

以Bittorrent应用为背景,对P2P网络中传统的节点选择策略进行了研究分析,指出了传统节点选择策略中存在的随机选择节点连接与交互以及交互过程中节点带宽利用率偏低的问题.对Tracker以外的节点来源如DHT、PEX节点来源的情况进行分析,以自身上传带宽利用率和网络中各节点的空闲带宽为参考,以减少带宽资源浪费、提高带宽利用率为目的.针对节点选择各阶段特点,设计并实现自适应节点选择机制,实验表明在对原系统的公平性影响很小的情况下,自适应机制能有效的减少网络中带宽资源浪费并将自身上传节点带宽利用率提高8.45％.小规模节点环境下(100节点)平均缩短节点下载完成时间6.7％,大规模下载环境下(500节点)平均缩短下载完成时间36.3％.有效的提高了系统中文件的获得和分发效力.     

A database approach for information communication in a peer‐to‐peer collaborative CAD environment

Timely and efficient information communication is a key factor in ensuring successful collaboration in engineering collaborative design. This work proposes a database approach to support information communication between distributed and autonomous CAD systems. It provides the designer with an easy and flexible way, a project‐based propagation meta‐table, to specify what parts of a CAD information model should be communicated to other collaborating designers. A CAD peer manager, containing a peer database that stores information to be exchanged with the other collaborators, wraps each participating CAD system. The peer manager identifies changes made to the CAD model by using stored procedures and active rules in the peer database that are automatically generated based on the propagation meta‐table. The identified updates are propagated in a timely manner to other peers via inter‐database message passing, thereby minimizing the volume of necessary information to be exchanged. Furthermore, remote peer designers can flexibly incorporate, filter, or delete received updates by using a propagation control interface, which is also used to issue user's commands to download the data from the CAD system to the peer database and lookup the received messages in the peer database. The approach is applicable on any CAD system having a CORBA interface and can also be applied to other kinds of object‐oriented interfaces. Copyright © 2007 John Wiley & Sons, Ltd.     

Top-k query processing for replicated data in mobile peer to peer networks

In mobile ad hoc peer to peer (M-P2P) networks, since nodes are highly resource constrained, it is effective to retrieve data items using a top-k query, in which data items are ordered by the score of a particular attribute and the query-issuing node acquires data items with the k highest scores. However, when network partitioning occurs, the query-issuing node cannot connect to some nodes having data items included in the top-k query result, and thus, the accuracy of the query result decreases. To solve this problem, data replication is a promising approach. However, if each node sends back its own data items (replicas) responding to a query without considering replicas held by others, same data items are sent back to the query-issuing node more than once through long paths, which results in increase of traffic. In this paper, we propose a top-k query processing method considering data replication in M-P2P networks. This method suppresses duplicate transmissions of same data items through long paths. Moreover, an intermediate node stops transmitting a query message on-demand.     

BitTorrent中一种基于全局贡献的节点选择策略

BitTorrent采用基于速率的Tit-For-Tat（Rate-based TFT）阻塞算法和乐观激活（Optimistic Unchoke,OU）算法为节点选择策略：上传节点采用Rate-based TFT算法选择为自身提供文件块上传速度最快的4个请求节点为下载节点,采用OU算法随机选择其他1个请求节点为下载节点。BitTorrent中Rate-based TFT算法只考虑邻居为上传节点所上传的文件块数即直接贡献,资源利用率不高,不能有效保证上传/下载之间的公平性。提出一种基于全局贡献的节点选择策略（Contribution-based TFT）,从直接贡献和间接贡献（即对其他节点所上传的文件块）两方面来考虑某段时间内节点的全局贡献,贡献越多,获取下载服务的优先权限越高。模拟实验表明,基于全局贡献的节点选择策略提高了上传配额利用率,减少了文件下载时间,并保证了公平性。     

Comparing the effectiveness of peer instruction to individual learning during a chromatography course

Peer instruction has been recognized as an instructional method having a positive impact on learning compared to traditional lectures in science. This method has been widely supported by the socio‐constructivist approach to learning giving a positive role to interaction between peers in the construction of knowledge. As far as we know, no study has been conducted from the socio‐cognitive approach which suggests that individuals working alone perform better than those interacting with others in groups. Thus, the aim of the present study was to examine whether peer instruction improves learning when compared with an individual learning method that does not require any interaction with peers. After being randomly divided into either a peer instruction or an individual learning condition in a chromatography course, students had to answer to a series of multiple‐choice questions using clickers at the beginning (pre‐test) and end of (post‐test) the session. Results revealed that the percentage of correct answers increased similarly from the pre‐ to the post‐test in both conditions. Nevertheless, students perceived the peer instruction method as being more satisfying, engaging and useful than the individual learning method. The findings revealed that peer instruction provides subjective benefits, but failed to demonstrate a greater learning gain.