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

• 作者: Fadai S. Ganjaliyev Ramiz M. Aliguliyev Rasim M. Alguliev
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 医学
• 关键词: OWA OPERATOR Orness DATA SOURCE
• 年，卷（期）: 2012,（2）
• 页码范围: 154-158
• 页数: 5页
• 分类号: R73

摘要

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.