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Discover Computing
Published in: Discover Computing 4/2014

01-08-2014

A survey of approaches for ranking on the web of data

Authors: Antonio J. Roa-Valverde, Miguel-Angel Sicilia

Published in: Discover Computing | Issue 4/2014

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Abstract

Ranking information resources is a task that usually happens within more complex workflows and that typically occurs in any form of information retrieval, being commonly implemented by Web search engines. By filtering and rating data, ranking strategies guide the navigation of users when exploring large volumes of information items. There exist a considerable number of ranking algorithms that follow different approaches focusing on different aspects of the complex nature of the problem, and reflecting the variety of strategies that are possible to apply. With the growth of the web of linked data, a new problem space for ranking algorithms has emerged, as the nature of the information items to be ranked is very different from the case of Web pages. As a consequence, existing ranking algorithms have been adapted to the case of Linked Data and some specific strategies have started to be proposed and implemented. Researchers and organizations deploying Linked Data solutions thus require an understanding of the applicability, characteristics and state of evaluation of ranking strategies and algorithms as applied to Linked Data. We present a classification that formalizes and contextualizes under a common terminology the problem of ranking Linked Data. In addition, an analysis and contrast of the similarities, differences and applicability of the different approaches is provided. We aim this work to be useful when comparing different approaches to ranking Linked Data and when implementing new algorithms.
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Footnotes
5
This classification has been taken from Delbru et al. (2010).
 
6
Note this differs from the intended notion of context agreed in this survey.
 
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Metadata
Title
A survey of approaches for ranking on the web of data
Authors
Antonio J. Roa-Valverde
Miguel-Angel Sicilia
Publication date
01-08-2014
Publisher
Springer Netherlands
Published in
Discover Computing / Issue 4/2014
Print ISSN: 2948-2984
Electronic ISSN: 2948-2992
DOI
https://doi.org/10.1007/s10791-014-9240-0

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