CLEAR: a credible method to evaluate website archivability

Web archiving is crucial to ensure that cultural, scientific and social heritage on the web remains accessible and usable over time. A key aspect of the web archiving process is optimal data extraction from target websites. This procedure is difficult for such reasons as, website complexity, plethora of underlying technologies and ultimately the open-ended nature of the web. The purpose of this work is to establish the notion of Website Archivability (WA) and to introduce the Credible Live Evaluation of Archive Readiness (CLEAR) method to measure WA for any website. Website Archivability captures the core aspects of a website crucial in diagnosing whether it has the potentiality to be archived with completeness and accuracy. An appreciation of the archivability of a web site should provide archivists with a valuable tool when assessing the possibilities of archiving material and in- uence web design professionals to consider the implications of their design decisions on the likelihood could be archived. A prototype application, archiveready.com, has been established to demonstrate the viabiity of the proposed method for assessing Website Archivability

A data mining approach for location prediction in mobile environments

Cataloged from PDF version of article.Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our threephase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods. 2004 Elsevier B.V. All rights reserved

BlogForever D5.3: User Questionnaires and Reports

This report presents the feedback gathered from third party users during the BlogForever Case Studies. Therefore, the research framework is defined and the case studies results are presented, followed by a summary of conclusions and remarks

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

A data mining approach for location prediction in mobile environments

Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our three-phase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods. © 2004 Elsevier B.V. All rights reserved

Locality and Bounding-Box Quality of Two-Dimensional Space-Filling Curves

Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different space-filling curves are for this purpose. We give general lower bounds on the bounding-box quality measures and on locality according to Gotsman and Lindenbaum for a large class of space-filling curves. We describe a generic algorithm to approximate these and similar quality measures for any given curve. Using our algorithm we find good approximations of the locality and the bounding-box quality of several known and new space-filling curves. Surprisingly, some curves with relatively bad locality by Gotsman and Lindenbaum's measure, have good bounding-box quality, while the curve with the best-known locality has relatively bad bounding-box quality.Comment: 24 pages, full version of paper to appear in ESA. Difference with first version: minor editing; Fig. 2(m) correcte

Off-Diagonal Geometric Phases

We investigate the adiabatic evolution of a set of non-degenerate eigenstates of a parameterized Hamiltonian. Their relative phase change can be related to geometric measurable quantities that extend the familiar concept of Berry phase to the evolution of more than one state. We present several physical systems where these concepts can be applied, including an experiment on microwave cavities for which off-diagonal phases can be determined from published data.Comment: 5 pages 2 figures - RevTeX. Revised version including geometrical interpretatio

Clustering mobile trajectories for resource allocation in mobile environments

The recent developments in computer and communication technologies gave rise to Personal Communication Systems. Due to the nature of the PCS, the bandwidth allocation problem arises, which is based on the notion of bandwidth-on-demand. We deal with the problem of how to predict the position of a mobile client. We propose a new algorithm, called DCP, to discover user mobility patterns from collections of recorded mobile trajectories and use them for the prediction of movements and dynamic allocation of resources. The performance of the proposed algorithm is examined against two baseline algorithms. The simulation results illustrate that the proposed algorithm achieves recall that is comparable to that of the baseline algorithms and substantial improvement in precision. This improvement guarantees very good predictions for resource allocation with the advantage of very low resource consumption. © Springer-Verlag Berlin Heidelberg 2003