A Novel Contextual Information Recommendation Model and Its Application in e-Commerce Customer Satisfaction Management

In the current supply chain environment, distributed cognition theory tells us that various types of context information in which a recommendation is provided are important for e-commerce customer satisfaction management. However, traditional recommendation model does not consider the distributed and differentiated impact of different contexts on user needs, and it also lacks adaptive capacity of contextual recommendation service. Thus, a contextual information recommendation model based on distributed cognition theory is proposed. Firstly, the model analyzes the differential impact of various sensitive contexts and specific examples on user interest and designs a user interest extraction algorithm based on distributed cognition theory. Then, the sensitive contexts extracted from user are introduced into the process of collaborative filtering recommendation. The model calculates similarity among user interests. Finally, a novel collaborative filtering algorithm integrating with context and user similarity is designed. The experimental results in e-commerce and benchmark dataset show that this model has a good ability to extract user interest and has higher recommendation accuracy compared with other methods

Semantically-aware data discovery and placement in collaborative computing environments

As the size of scientific datasets and the demand for interdisciplinary collaboration grow in modern science, it becomes imperative that better ways of discovering and placing datasets generated across multiple disciplines be developed to facilitate interdisciplinary scientific research. For discovering relevant data out of large-scale interdisciplinary datasets. The development and integration of cross-domain metadata is critical as metadata serves as the key guideline for organizing data. To develop and integrate cross-domain metadata management systems in interdisciplinary collaborative computing environment, three key issues need to be addressed: the development of a cross-domain metadata schema; the implementation of a metadata management system based on this schema; the integration of the metadata system into existing distributed computing infrastructure. Current research in metadata management in distributed computing environment largely focuses on relatively simple schema that lacks the underlying descriptive power to adequately address semantic heterogeneity often found in interdisciplinary science. And current work does not take adequate consideration the issue of scalability in large-scale data management. Another key issue in data management is data placement, due to the increasing size of scientific datasets, the overhead incurred as a result of transferring data among different nodes also grow into a significant inhibiting factor affecting overall performance. Currently, few data placement strategies take into consideration semantic information concerning data content. In this dissertation, we propose a cross-domain metadata system in a collaborative distributed computing environment and identify and evaluate key factors and processes involved in a successful cross-domain metadata system with the goal of facilitating data discovery in collaborative environments. This will allow researchers/users to conduct interdisciplinary science in the context of large-scale datasets that will make it easier to access interdisciplinary datasets, reduce barrier to collaboration, reduce cost of future development of similar systems. We also investigate data placement strategies that involve semantic information about the hardware and network environment as well as domain information in the form of semantic metadata so that semantic locality could be utilized in data placement, that could potentially reduce overhead for accessing large-scale interdisciplinary datasets

Configuration management for a distributed and collaborative software development environment

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.Includes bibliographical references (leaves 104-106).In the face of changing technology, the world is becoming more global by the minute. This globalization has resulted in dispersed teams and collaborative opportunities, which offer value and depth to projects. Software development also reflects this globalization, as do all the processes involved in software development. It is important to understand these changes and how they affect not only the entire development process as a whole but also each individual part of the process. Configuration management is an integral part of the software development process. In order to perform good software development, it is imperative to understand and be able to implement proper configuration management. Thus, as configuration management is important to software development, it is also important to study the effects of how the changing context of software development toward distributed and collaborative environments affects configuration management. Not only does configuration management influence the transition to this type of environment, it also is quite affected by it. In this thesis, I aim to examine the impact of a distributed and collaborative development environment on configuration management. I will first give an overview of software engineering with respect to configuration management; next, I will provide and introduction to traditional configuration management, and in the following chapter, I will discuss distributed and collaborative configuration management as it exists today. Next, I will provide a case study of the ieCollab project, a project in which developers were dispersed and a great deal of collaboration occurred, and finally, I will discuss the future of collaborative and distributed configuration management.by Teresa Liu.M.Eng

Distributed cognition applied to the empirical analysis of computer supported collaborative kowledge management interactions

In the field of Human Computer Interaction, and more specifically in the field of Computer Supported Collaborative Work and Knowledge Management, cognitive and sociological dimensions cannot be neglected in the design of value analysis. The material and social environment models almost all cognitive processes because the vast majority of them are mediated by the interaction with other agents and other artifacts. Computers connected to the Internet, are becoming fundamental elements of these interactions. Following these premises, in this paper, a methodological framework is applied, called MAIA (Methodology for the analysis of the interaction between agents of a socio-technical system), structured and based on distributed cognition in order to facilitate the analysis of a collaborative Web system oriented to knowledge management in an academic context, at high university level. Specifically, the analysis focuses on the interactions of cognitive agents that occur during the cycle of knowledge management (activities to use, create, distribute and share knowledge), and on how they affect coordination, communication and collaboration, key aspects of group work.XI Workshop de Ingeniería de SoftwareRed de Universidades con Carreras de Informática (RedUNCI

Distributed cognition applied to the empirical analysis of computer supported collaborative kowledge management interactions

In the field of Human Computer Interaction, and more specifically in the field of Computer Supported Collaborative Work and Knowledge Management, cognitive and sociological dimensions cannot be neglected in the design of value analysis. The material and social environment models almost all cognitive processes because the vast majority of them are mediated by the interaction with other agents and other artifacts. Computers connected to the Internet, are becoming fundamental elements of these interactions. Following these premises, in this paper, a methodological framework is applied, called MAIA (Methodology for the analysis of the interaction between agents of a socio-technical system), structured and based on distributed cognition in order to facilitate the analysis of a collaborative Web system oriented to knowledge management in an academic context, at high university level. Specifically, the analysis focuses on the interactions of cognitive agents that occur during the cycle of knowledge management (activities to use, create, distribute and share knowledge), and on how they affect coordination, communication and collaboration, key aspects of group work.XI Workshop de Ingeniería de SoftwareRed de Universidades con Carreras de Informática (RedUNCI

Telefacturing Based Distributed Manufacturing Environment for Optimal Manufacturing Service by Enhancing the Interoperability in the Hubs

Recent happenings are surrounding the manufacturing sector leading to intense progress towards the development of effective distributed collaborative manufacturing environments. This evolving collaborative manufacturing not only focuses on digitalisation of this environment but also necessitates service-dependent manufacturing system that offers an uninterrupted approach to a number of diverse, complicated, dynamic manufacturing operations management systems at a common work place (hub). This research presents a novel telefacturing based distributed manufacturing environment for recommending the manufacturing services based on the user preferences. The first step in this direction is to deploy the most advanced tools and techniques, that is, Ontology-based Protege 5.0 software for transforming the huge stored knowledge/information into XML schema of Ontology Language (OWL) documents and Integration of Process Planning and Scheduling (IPPS) for multijobs in a collaborative manufacturing system. Thereafter, we also investigate the possibilities of allocation of skilled workers to the best feasible operations sequence. In this context, a mathematical model is formulated for the considered objectives, that is, minimization of makespan and total training cost of the workers. With an evolutionary algorithm and developed heuristic algorithm, the performance of the proposed manufacturing system has been improved. Finally, to manifest the capability of the proposed approach, an illustrative example from the real-time manufacturing industry is validated for optimal service recommendation.This work has been supported by by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Facilitating social collaboration in mobile cloud-based learning: a teamwork as a service (TaaS) approach

Mobile learning is an emerging trend that brings many advantages to distributed learners, enabling them to achieve collaborative learning, in which the virtual teams are usually built to engage multiple learners working together towards the same pedagogical goals in online courses. However, the socio-technical mechanisms to enhance teamwork performance are lacking. To meet this gap, we adopt the social computing to affiliate learners’ behaviors and offer them computational choices to build a better collaborative learning context. Combining the features of the cloud environment, we have identified a learning flow based on Kolb team learning experience to realize this approach. Such novel learning flow can be executed by our newly designed system, Teamwork as a Service (TaaS), in conjunction with the cloud-hosting learning management systems. Following this learning flow, learners benefit from the functions provided by cloud-based services when cooperating in a mobile environment, being organized into cloud-based teaching strategies namely “Jigsaw Classroom”, planning and publishing tasks, as well as rationalizing task allocation and mutual supervision. In particular, we model the social features related to the collaborative learning activities, and introduce a genetic algorithm approach to grouping learners into appropriate teams with two different team formation scenarios. Experimental results prove our approach is able to facilitate teamwork, while learners’ capabilities and preferences are taken into consideration. In addition, empirical evaluations have been conducted to show the improvement of collaborative learning brought by TaaS in real university level courses

Confronting the grand challenge of environmental sustainability within supply chains: How can organizational strategic agility drive environmental innovation?

Supply chains are interconnected, globally distributed, and complex systems that significantly impact the environment and human civilization. Achieving environmental sustainability in supply chains is a grand challenge that requires collaboration and innovation among multiple stakeholders. In this study, we combine the natural-resource-based view and the stakeholder-resource-based view (SRBV) to examine how organizational strategic agility can foster collaborative environmental innovation and enhance environmental sustainability in supply chains. We use data from 758 managers from 185 firms in Turkey, an emerging economy context. We find that organizational strategic agility, enabled by organic organizational structures and regional innovation initiatives, leads to more collaborative environmental innovation with supply partners and higher environmental sustainability performance. Our study contributes to the literature on grand challenges, organizational strategic agility, and innovation management by showing how for-profit firms can leverage their strategic agility to address the grand challenge of environmental sustainability in supply chains. We also find two interventions to promote this form of environmental innovation: developing organizational strategic agility and organic structures within firms and involvement in regional innovation initiatives to stimulate collaborative innovation for environmental sustainability among supply partners

Cooperative Trust Framework for Cloud Computing Based on Mobile Agents

Cloud computing opens doors to the multiple, unlimited venues from elastic computing to on demand provisioning to dynamic storage, reduce the potential costs through optimized and efficient computing. To provide secure and reliable services in cloud computing environment is an important issue. One of the security issues is how to reduce the impact of for any type of intrusion in this environment. To counter these kinds of attacks, a framework of cooperative Hybrid intrusion detection system (Hy-IDS) and Mobile Agents is proposed. This framework allows protection against the intrusion attacks. Our Hybrid IDS is based on two types of IDS, the first for the detection of attacks at the level of virtual machines (VMs), the second for the network attack detection and Mobile Agents. Then, this framework unfolds in three phases: the first, detection intrusion in a virtual environment using mobile agents for collected malicious data. The second, generating new signatures from malicious data, which were collected in the first phase. The third, dynamic deployment of updates between clusters in a cloud computing, using the newest signatures previously created. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively. In this paper, we develop a collaborative approach based on Hy-IDS and Mobile Agents in Cloud Environment, to define a dynamic context which enables the detection of new attacks, with much detail as possible

Quality of service management in service-oriented grids

Grid computing provides a robust paradigm for aggregating disparate resources in a secure and controlled environment. The emerging grid infrastructure gives rise to a class of scientific applications and services in support of collaborative and distributed resource-sharing requirements, as part of teleimmersion, visualization and simulation services. Because such applications operate in a collaborative mode, data must be stored, processed and delivered in a timely manner. Such classes of applications have collaborative and distributed resource-sharing requirements, and have stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is therefore essential to orchestrate and guarantee the interaction among such applications in a distributed computing environment. Grid architectures require an underpinning of QoS support to manage complex computation-intensive and data-intensive applications, as current grid middleware solutions lack QoS provision. QoS guarantees in the grid context have, however, not been given the importance they merit. To enhance its functionality, a computational grid must be overlaid with an advanced QoS architecture to best execute those applications with real-time constraints. This thesis reports on the design and implementation of a software framework, called Grid QoS Management (G-QoSm). G-QoSm incorporates a new QoS management model and provides a service-oriented QoS management approach that supports the Open Grid Service Architecture. Its novel features include grid-service discovery based on QoS attributes, immediate and advance resource reservation, service execution with QoS constraints, and techniques for QoS adaptation to compensate for resource degradation, and to optimise resource allocation while maintaining a service level agreement. The benefits of G-QoSm are demonstrated by prototype test-beds that integrate scientific grid applications and simulate grid data-transfer applications. Results show that the grid application and the data-transfer simulation have better performance when used with the proposed QoS approach. QoS abstractions are presented for building QoS-aware applications, in the context of service-oriented grids. These abstractions are application programming interfaces to facilitate application developers utilising the proposed QoS management solution.EThOS - Electronic Theses Online ServiceGBUnited Kingdo