Aggregating Edge Weights in Social Networks on the Web Extracted from Multiple Sources with Different Importance Degrees

Alguliev, Rasim M. and Aliguliyev, Ramiz M. and Ganjaliyev, Fadai S. (2012) Aggregating Edge Weights in Social Networks on the Web Extracted from Multiple Sources with Different Importance Degrees. Journal of Intelligent Learning Systems and Applications, 04 (02). pp. 154-158. ISSN 2150-8402

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Abstract

Information on a given set of entities can be derived from multiple sources on the Web. Social networks built from these sources, using these entities as nodes, will have different edge weight values, although the entities will be the same. If these sources are different, one will not normally trust each of them equally. One source will be considered more or less importance than the other. Completely ignoring sources with little importance may yield unexpected results. In this paper, we propose a method for aggregating weight values for social networks built from the Web using different sources. First, multiple social networks are built from different data sources. Then the received edge weights are aggregated, with the importance of a data source taken into account.

Item Type: Article
Subjects: STM Open Press > Engineering
Depositing User: Unnamed user with email support@stmopenpress.com
Date Deposited: 30 Jan 2023 10:12
Last Modified: 20 Jun 2024 13:22
URI: http://journal.submissionpages.com/id/eprint/194

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