Distributed recommender for peer-to-peer knowledge sharing

A novel model of distributed knowledge recommender system is proposed to facilitate knowledge sharing among collaborative team members. Different from traditional recommender systems in the client-server architecture, our model is oriented to the peer-to-peer (P2P) environment without the centralized control. Among the P2P network of collaborative team members, each peer is deployed with one distributed knowledge recommender, which can supply proper knowledge resources to peers who may need them. This paper investigates the key techniques for implementing the distributed knowledge recommender model. Moreover, a series of simulation-based experiments are conducted by using the data from a real-world collaborative team in an enterprise. The experimental results validate the efficiency of the proposed model. This research paves the way for developing platforms that can share and manage large-scale distributed knowledge resources. This study also provides a new framework for simulating and studying individual or organizational behaviors of knowledge sharing in a collaborative team.     

Collaborative technologies in knowledge telework: an exploratory study

Abstract.  Knowledge workers in distributed work environments require substantial communication with colleagues and supervisors to perform their work activities, and collaborative technologies, like groupware, continue to improve the potential for such communication. This study investigates how an improvement in collaborative technology among a group of knowledge teleworkers impacts their communication patterns. The study focuses on one communication-based work process: knowledge sharing. The research involves a 6-month exploratory longitudinal case study of a group of teleworkers where a new groupware technology was implemented. The results indicate that while there are fewer instances of communication among group members after the technology is implemented, communication becomes more centralized around the district manager. These results suggest that increased collaborative technologies result in an adjustment between explicit and tacit knowledge sharing, as the availability of a centralized and updateable database reduces workgroup communications. However, consistent with structuration theory, telework group members do use communication technologies to address their most apparent needs and concerns. Other potential explanations and implications of these findings are discussed.     

Collaborative filtering based on workflow space

The traditional recommender systems are usually oriented to general situations in daily lives (e.g. recommend movies, books, music, news and etc.), but seldom cover the recommendation scenarios for the collaborative team environments. We have done an explorative study on collaborative filtering mechanism for collaborative team environments, which is some kind of multi-dimensional recommender systems problem with consideration of workflow context. This paper proposed 3-dimensional workflow space model, and investigated the new similarities measure between members in workflow space. Then, the new similarities measure is utilized into collaborative filtering for recommender systems in collaborative team environments. At last, the efficiency and usability of the proposed method are validated by experiments referring to a real-world collaborative team of a manufacturing enterprise.     

Effect of knowledge sharing visibility on incentive-based relationship in Electronic Knowledge Management Systems: An empirical investigation

Previous studies have confirmed the knowledge sharing visibility (KSV) may ensure the incentive-sharing relationship within traditional organizations. However, considering high loafing tendency in IT-based and distributed environments, this effect should be re-examined. This study examines how KSV impacts on incentive-based relationship in IT-based knowledge management systems. The data were collected from real KM systems in an innovative service company. The results show that, in distributed environment, KSV was still a critical moderators in the prediction of employee’s knowledge sharing behaviors. In the electronic KMS environment, the positive relationship between incentive and KS is stronger when employees’ perceived KSV is higher. This research contributes theoretically to KS literature in examing the KSV as the three-way moderators on incentive-based relationship in IT-based environment, from real organizational samples.     

A hybrid recommendation algorithm adapted in e-learning environments

With the rapid development of online learning technology, a huge amount of e-learning materials have been generated which are highly heterogeneous and in various media formats. Besides, e-learning environments are highly dynamic with the ever increasing number of learning resources that are naturally distributed over the network. On the other hand, in the online learning scenario, it is very difficult for users without sufficient background knowledge to choose suitable resources for their learning. In this paper, a hybrid recommender system is proposed to recommend learning items in users’ learning processes. The proposed method consists of two steps: (1) discovering content-related item sets using item-based collaborative filtering (CF), and (2) applying the item sets to sequential pattern mining (SPM) algorithm to filter items according to common learning sequences. The two approaches are combined to recommend potentially useful learning items to guide users in their current learning processes. We also apply the proposed approach to a peer-to-peer learning environment for resource pre-fetching where a central directory of learning items is not available. Experiments are conducted in a centralized and a P2P online learning systems for the evaluation of the proposed method and the results show good performance of it.     

Individual characteristics influencing the sharing of knowledge on social networking services: online identity,self-efficacy,and knowledge sharing intentions

ABSTRACT

Social media have become an important place for individuals with similar interests to exchange opinions and share resources. Ubiquitous collaborative learning environments in SNS have great educational and organisational potential and offer a platform for sharing knowledge. Rising interest in personal factors in knowledge management research calls for a better understanding of how knowledge is shared in SNS-based collaborative learning. Grounded on the theories of planned behaviour and social identity, this study investigates individual characteristics that affect the sharing of knowledge in SNS learning communities. The study also examines whether intent to share knowledge mediates those personal characteristics and sharing of knowledge. Eighty individuals from five active Facebook groups participated in this study. The findings indicate that individual characteristics, such as online personal identity, web-specific self-efficacy, and knowledge-creation self-efficacy significantly predict sharing of knowledge. In addition, intent to share knowledge mediates between the sharing of knowledge and online identity, web-specific self-efficacy, or knowledge-creation self-efficacy. The results reveal a need for customised support and environmental design focusing on online personal identity, web-specific self-efficacy, knowledge-creation self-efficacy, and intent to share knowledge in a knowledge-sharing community on SNS. Implications for the SNS communities and suggestions for further research are discussed.     

Investigating Knowledge Management practices in software development organisations – An Australian experience

This study, using both quantitative and qualitative methods, investigates current practice of Knowledge Management (KM) in Software Engineering (SE) processes in two Australian companies on the basis that they both claimed to apply KM practices in their software development work. It also describes the KM activities and KM process used in SE practice, and examines the enablers of KM process for SE in terms of leadership, technology, culture, process and measurement.One of the main findings showed that software developers believe in the usefulness of knowledge sharing; however, their ability to utilise some of the KM systems was limited. The most commonly used systems included personal networks, informal networks, groupware and third-party knowledge. There is a need to formalise knowledge sharing of practices, while also supporting informal and ad-hoc knowledge sharing. While KM was considered to be important, the tools, techniques and methodologies currently employed for software development were inadequate to address effective management of knowledge in these organisations. In both organisations, a uniform model of the KM process did not exist. Among the four KM enablers, leadership was considered to be the most significant as top-down KM strategies were seemingly being pursued by management. Technology was also considered to be an obvious mechanism for KM, despite some of their current KM systems either being unsuitable or inaccessible. In addition, the crucial role that personal networks played in accessing tacit and implicit knowledge was seen as a key reason to foster a culture that encourages participants to share their knowledge with others.     

Reputation-based dependable scheduling of workflow applications in Peer-to-Peer Grids

Grids facilitate creation of wide-area collaborative environment for sharing computing or storage resources and various applications. Inter-connecting distributed Grid sites through peer-to-peer routing and information dissemination structure (also known as Peer-to-Peer Grids) is essential to avoid the problems of scheduling efficiency bottleneck and single point of failure in the centralized or hierarchical scheduling approaches. On the other hand, uncertainty and unreliability are facts in distributed infrastructures such as Peer-to-Peer Grids, which are triggered by multiple factors including scale, dynamism, failures, and incomplete global knowledge.In this paper, a reputation-based Grid workflow scheduling technique is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Peer-to-Peer Grid environments. The proposed approach builds upon structured peer-to-peer indexing and networking techniques to create a scalable wide-area overlay of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers mediated via Grid resource brokers. The proposed algorithm dynamically adapts to changing resource conditions and offers significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. The results evaluated through an extensive trace driven simulation show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.     

Mapping knowledge sharing traits to business strategy in knowledge based organisation

Globalization has resulted in increasing use of knowledge as competitive weapon in many organizations nowadays. In this context, an increasing number of organizations are focusing on communities of practice (CoPs) orientated knowledge management (KM) studies and the links between KM and organizational business strategy. This link is an important determinant of organizational performance. While KM business strategy (linked to organization business strategy) is important, knowledge sharing behavior of knowledge workers is a critical enabler of effective knowledge management and organizational performance. That is, organizations invest resources in creating CoPs for competitive advantage and lack of suitable candidates will result in loss of momentum and less knowledge sharing in CoPs and there by underutilizing the resources. The aim of this research is to identify the personality traits to portrait the features of knowledge workers suitable for CoPs oriented KM and business strategy. Four KM business strategies have been established in this paper in light of organization performance orientation and KM implementation mode and traits of knowledge workers are mapped to different business strategies. The most significant personality traits of knowledge sharing behavior have been analyzed to determine the suitable traits for different type business strategies. Thus contributions of this paper include (a) defining a model which links four business strategies with CoPs orientated KM model and knowledge sharing behavior model (based on revised Five Factor Model); (b) mapping of personality traits of knowledge workers with four business strategies; (c) providing a guideline to knowledge based organizations for seamless integration of business strategy with CoPs oriented KM and compatible knowledge workers and d) more effective utilization of organizational resources to facilitate improvement in organizational performance.     

Identifying knowledge agents in a KM strategy: the use of the structural influence index

Knowledge transfer is a complex KM activity that integrates communication technologies with challenging social, cultural, and organizational issues. It is critical to effective KM systems (KMS) and the development of effective transfer strategies enhances competitive advantage. This study incorporated the theory of organizational influence to demonstrate the structural influence index within a network KMS. Using the research process in the pharmaceutical industry as a basis for knowledge transfer events, this study demonstrated the benefits of structural indexing, which identifies knowledge agents, evaluates knowledge sharing among organizational members, and objectively assesses the contribution of knowledge agents. Subgrouping knowledge agents gave insight into knowledge sharing among members and provided a basis for the coordination of knowledge resources in new and unique ways.     

Knowledge Management Models within Information Technology Projects

The purpose of this study is to address the use of knowledge management (KM) in project management (PM) to improve the success of IT projects in achieving organizational goals. The conceptual framework included the project knowledge management (PKM) model, which helped identify the knowledge sharing in IT software projects for a local insurance company in Baltimore, Maryland. Interview data were collected from 26 IT project stakeholders. The analysis revealed four themes of managing knowledge in the requirement process, code development process, testing process, and the helpdesk process for the success of the IT project. Each of the four processes used different KM repositories and face-to-face tools.     

Mining knowledge demands from information flow

Among a collaborative team, members usually come from diverse disciplines, and their demands for knowledge are also different from each other. Information flow is a type of collaborative process, which exists behind every collaborative team. This paper is concerned with how to obtain team members’ knowledge demands from the information flow. Firstly, the knowledge demands model is defined. Based on the model of knowledge demands and information filtering technologies, some approaches for mining demands from information flow are proposed. This study on the knowledge demand mining can pave the way for developing knowledge recommender systems, which can recommend proper knowledge to proper team members with a collaborative team.     

Application of KM measures to the impact of a specialized groupware system on corporate productivity and operations

Here we describe an experiment to show the improvement in productivity resulting from use of a specialized groupware system, using quantitative data and observations of the knowledge management (KM) processes, styles, and critical success factors. Data describing the work process before and after the deployment of the system was applied to measure the impact on performance, operations, and knowledge sharing behavior. The attitude of the organization toward knowledge sharing and the deployed groupware system was then studied along several dimensions that represent KM styles, by assessing the KM orientation and motivation of the organization. Lessons learned were presented and used for directing the attention of management to the importance of supporting collaborative and KM technologies for corporate strategic competitiveness.     

FlexiFrag: A design pattern for flexible file sharing in distributed collaborative applications

The need for flexible file sharing in distributed systems is increasing in applications such as calendar management, collaborative editing of documents, collaborative software developments etc. The file sharing policies required in these applications are often very different from the traditional read/write policies. Hence, a flexible way of specifying and implementing sharing policies on individual files in file systems is required. We propose a distributed object-based system model of constructing file systems. The object-based system model is based on a pattern called FlexiFrag. We show how a distributed object-based system and in particular distributed file system can be constructed using the pattern in a flexible way.     

An analysis of peer similarity for recommendations in P2P systems

In this paper, we propose a novel recommender framework for partially decentralized file sharing Peer-to-Peer systems. The proposed recommender system is based on user-based collaborative filtering. We take advantage from the partial search process used in partially decentralized systems to explore the relationships between peers. The proposed recommender system does not require any additional effort from the users since implicit rating is used. The recommender system also does not suffer from the problems that traditional collaborative filtering schemes suffer from like the Cold start and the Data sparseness. To measure the similarity between peers, we propose Files?? Popularity Based Recommendation (FP) and Asymmetric Peers?? Similarity Based Recommendation with File Popularity (ASFP). We also investigate similarity metrics that were proposed in other fields and adapt them to file sharing P2P systems. We analyze the impact of each similarity metric on the accuracy of the recommendations. Both weighted and non weighted approaches were studied.     

Expert Recommender: Designing for a Network Organization

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge-intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.     

Preventing Recommendation Attack in Trust-Based Recommender Systems

Despite its success, similarity-based collaborative filtering suffers from some limitations, such as scalability, sparsity and recommendation attack. Prior work has shown incorporating trust mechanism into traditional collaborative filtering recommender systems can improve these limitations. We argue that trust-based recommender systems are facing novel recommendation attack which is different from the profile injection attacks in traditional recommender system. To the best of our knowledge, there has not any prior study on recommendation attack in a trust-based recommender system. We analyze the attack problem, and find that “victim” nodes play a significant role in the attack. Furthermore, we propose a data provenance method to trace malicious users and identify the “victim” nodes as distrust users of recommender system. Feasibility study of the defend method is done with the dataset crawled from Epinions website.     

基于ROA的移动个人知识管理系统集成

针对目前个人知识管理工具存在的功能单一以及实时性差等缺陷,提出基于智能化移动终端的、敏捷实时的个人知识管理体系结构.通过与传统基于SOA的Web服务进行比较,阐述基于ROA的Web服务在系统可扩展性、安全性及交互性等方面的优势.在此基础上,提出移动个人知识管理平台与现有第三方知识管理系统之间的集成方案,采用J2EE、JQUERY、RESTLET和ANDROID等开发环境搭建个人知识管理系统,给出异构知识管理平台之间相互集成的关键技术.     

基于业务抽象规划的分布式动态服务组合算法

异构系统间难以实现计算资源的灵活共享,制约分布式信息系统性能的提升,基于面向服务架构的Web服务技术,为异构系统计算资源共享提供了有效手段。为此,针对Web服务组合在集中式发布架构下单点故障和性能瓶颈问题,提出一种基于业务抽象规划的分布式动态服务组合算法。该算法根据组合规划结果对业务抽象规划库进行动态扩充,快速组合出满足需求的服务,逐步提高服务组合响应率。仿真结果表明,该算法在分布式环境下可减少服务请求过程中交互的信息量,降低请求响应时间,提高服务组合效率。     

分布式协作模型及应用研究

With the development of the Web technology,the application environment has acquired many new characters such as dynamic, openness,distribution and information uncertainty.The processing mode of application systems is more complicated than ever.For example,it requires application systems to have more community processing ability,interactive ability,distributed processing ability and collaborative ability.Accordingly the research and development of the computer application system transited from client/server information processing system into distributed collaborative processing system based on Web.Especially in the environment where the information and resources are highly distributed,the accomplishment of complicated tasks is dependent more on the resources coordination,information sharing and coordinator collaboration.The collaboration is one aspect of the group behavior and its goal is to provide a optimal method to utilize the resource through the information interaction and to solve the task which couldn't be accomplished by each coordinator alone and get the more total benefits than the sum of each benefit.The collaboration problem is the important one for distributed tasks processing.This paper surveys,the research and application status of distributed collaborative models and several representative architectures of distributed collaborative processing are proposed.However,the existing problems and the future researching direction are presented.