Locating experts via online social networks

Online social networking systems provide indirect access to a large number of people connected by multi-step chains of acquaintances, and plays an important role in the referrals for human information flow. In this paper, from a networking point of view, we study the problem of locating experts for relevant information via online social networks. We model the action of forwarding a question with random walk, adjusted by a node's awareness of the potential expertise of his immediate neighbours. Using the model we derive analytical expressions of the performance metrics of a referral session in terms of the nodes' awareness level of their neighbours and the percentage of nodes that may have answers to the posed question. We also utilize several real online social networks to study the modeled question-forwarding strategy, and find that the simulation results validate our analyses. ©2010 IEEE.published_or_final_versionThe IEEE International Conference on Communications (ICC) 2010, Cape Town, South Africa, 23-27 May 2010. In Proceedings of the IEEE ICC, 2010, p. 1-

Design issues for agent-based resource locator systems

While knowledge is viewed by many as an asset, it is often difficult to locate particularitems within a large electronic corpus. This paper presents an agent based framework for the location of resources to resolve a specific query, and considers the associated design issue. Aspects of the work presented complements current research into both expertise finders and recommender systems. The essential issues for the proposed design are scalability, together ith the ability to learn and adapt to changing resources. As knowledge is often implicit within electronic resources, and therefore difficult to locate, we have proposed the use of ontologies, to extract the semantics and infer meaning to obtain the results required. We explore the use of communities of practice, applying ontology-based networks, and e-mail message exchanges to aid the resource discovery process

A pedagogy of abundance

The digitisation of content combined with a global network for delivery and an open system for sharing has seen radical changes in many industries. The economic model which has underpinned many content based industries has been based on an assumption of scarcity. With a digital, open, networked approach we are witnessing a shift to abundance of content, and subsequently new economic models are being developed which have this as an assumption. In this article the role of scarcity in developing higher education practice and pedagogy is explored. The shift to abundant content has as profound implications for education as it has for content industries. The possible contenders for a ‘pedagogy of abundance’ are examined and the necessary requirements for such a pedagogy outlined

Applying Science Models for Search

The paper proposes three different kinds of science models as value-added services that are integrated in the retrieval process to enhance retrieval quality. The paper discusses the approaches Search Term Recommendation, Bradfordizing and Author Centrality on a general level and addresses implementation issues of the models within a real-life retrieval environment.Comment: 14 pages, 3 figures, ISI 201

Second-Level Digital Divide: Mapping Differences in People's Online Skills

Much of the existing approach to the digital divide suffers from an important limitation. It is based on a binary classification of Internet use by only considering whether someone is or is not an Internet user. To remedy this shortcoming, this project looks at the differences in people's level of skill with respect to finding information online. Findings suggest that people search for content in a myriad of ways and there is a large variance in how long people take to find various types of information online. Data are collected to see how user demographics, users' social support networks, people's experience with the medium, and their autonomy of use influence their level of user sophistication.Comment: 29th TPRC Conference, 200

Science and Technology in Media

Tato práce se zabývá vlivem médií, především nových médií, na oblast vědy a techniky. Definuje základní mediální pojmy a upozorňuje na to, že média mohou být výborným prostředkem k propagaci vědy a techniky, ale mají také obrovskou moc a mohou zkreslovat realitu a manipulovat s lidmi. V práci je také rozebráno několik konkrétních příkladů. V závěru práce je nastíněn možný pohled do budoucna propojení vědy, techniky a médií.This thesis deals with the influence of Media, especially New Media, on the field of Science and Technology. It defines basic media terms and warns that Media may represent an excellent mean of Science and Technology promotion. On the other hand, they are very powerful and can distort reality and manipulate with humans. There are explored several examples in the thesis, too. The conclusion outlines a possible view on the interconnection of Science, Technology and Media in the future.

Chemical reaction optimization for the grid scheduling problem

Grid computing collects geographically dispersed resources ranging from laptops to supercomputers to compute tasks requested by clients. Grid scheduling, i.e., assigning tasks to resources, is an NP-hard problem, and thus, metaheuristic methods are employed to find the optimal solutions. In this paper, we propose a Chemical Reaction Optimization (CRO) algorithm for the grid scheduling problem. CRO is a population-based metaheuristics mimicking the interactions between molecules in a chemical reaction. We compare the CRO approach with four generally acknowledged metaheuristics, and show that CRO performs the best. ©2010 IEEE.published_or_final_versionThe IEEE International Conference on Communications (ICC) 2010, Cape Town, South Africa, 23-27 May 2010. In Proceedings of the IEEE ICC, 2010, p. 1-

Information Gathering in Networks via Active Exploration

How should we gather information in a network, where each node's visibility is limited to its local neighborhood? This problem arises in numerous real-world applications, such as surveying and task routing in social networks, team formation in collaborative networks and experimental design with dependency constraints. Often the informativeness of a set of nodes can be quantified via a submodular utility function. Existing approaches for submodular optimization, however, require that the set of all nodes that can be selected is known ahead of time, which is often unrealistic. In contrast, we propose a novel model where we start our exploration from an initial node, and new nodes become visible and available for selection only once one of their neighbors has been chosen. We then present a general algorithm NetExp for this problem, and provide theoretical bounds on its performance dependent on structural properties of the underlying network. We evaluate our methodology on various simulated problem instances as well as on data collected from social question answering system deployed within a large enterprise.Comment: Longer version of IJCAI'15 pape