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Abstract. Merging related RSS news (coming from one or different sources) is beneficial for end-users with different backgrounds (journalists, economists, etc.), particularly those accessing similar information. In this paper, we provide a practical approach to both: measure the relatedness, and identify relationships between RSS elements. Our approach is based on the concepts of semantic neighborhood and vector space model, and considers the content and structure of RSS news items.

Merging XML documents can be of key importance in several applications. For instance, merging the RSS news from same or different sources and providers can be beneficial for end-users in various scenarios. In this paper, we address this issue and explore the relatedness measure between RSS elements. We show here how to define and compute exclusive relations between any two elements and provide several predefined merging operators that can be extended and adapted to human needs. We also provide a set of experiments conducted to validate our approach.