72,741 research outputs found

    An Agent-Based Approach for Integrating User Profile Into a Knowledge Management Process

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    This paper presents an approach based on a user agent to permit a number of users connected to distant machines to access different information sources in order to satisfy their requests. This user agent permits the simplification of the information search from distributed sources by making them transparent to the users. The agent considers the specific needs of each user during the search and responds with reference to their profile. It also permits the processing of one or more information requests by one or more users, as well as concurrent responses to each of them. Moreover, the agent provides its users with a measure of interaction, in order to enhance the quality and quantity of the results obtained. As a result, the agent is endowed with the ability to filter and refine the search, thus improving its service to the users

    A system to support dissemination of knowledge and sharing of experiences in the working environment

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    In the information era enterprises strive to be productive and efficient. One feature of this goal is to engage their employees in education programmes, help them gain new experiences and knowledge and adapt to an ever-changing working environment. Such programmes require thorough design in order to achieve satisfactory results. Lately, enterprises recognising the role technology can play in the education of their employees, have adopted systems that supplement the traditional educational model with mechanisms that enable the sharing of experiences and knowledge [5]. In this paper we describe an architecture and a system prototype that allows users to search easily for information, interact with colleagues and share experiences, to compose and disseminate best practices and knowledge. The design of this system is based on insights gained from the operation of the Greek Taxation System

    Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study

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    Recommender systems engage user profiles and appropriate filtering techniques to assist users in finding more relevant information over the large volume of information. User profiles play an important role in the success of recommendation process since they model and represent the actual user needs. However, a comprehensive literature review of recommender systems has demonstrated no concrete study on the role and impact of knowledge in user profiling and filtering approache. In this paper, we review the most prominent recommender systems in the literature and examine the impression of knowledge extracted from different sources. We then come up with this finding that semantic information from the user context has substantial impact on the performance of knowledge based recommender systems. Finally, some new clues for improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.3, August 201

    A review on massive e-learning (MOOC) design, delivery and assessment

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    MOOCs or Massive Online Open Courses based on Open Educational Resources (OER) might be one of the most versatile ways to offer access to quality education, especially for those residing in far or disadvantaged areas. This article analyzes the state of the art on MOOCs, exploring open research questions and setting interesting topics and goals for further research. Finally, it proposes a framework that includes the use of software agents with the aim to improve and personalize management, delivery, efficiency and evaluation of massive online courses on an individual level basis.Peer ReviewedPostprint (author's final draft

    Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module

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    Diverse recommendation techniques have been already proposed and encapsulated into several e-business applications, aiming to perform a more accurate evaluation of the existing information and accordingly augment the assistance provided to the users involved. This paper reports on the development and integration of a recommendation module in an agent-based transportation transactions management system. The module is built according to a novel hybrid recommendation technique, which combines the advantages of collaborative filtering and knowledge-based approaches. The proposed technique and supporting module assist customers in considering in detail alternative transportation transactions that satisfy their requests, as well as in evaluating completed transactions. The related services are invoked through a software agent that constructs the appropriate knowledge rules and performs a synthesis of the recommendation policy
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