Learning to Find Interesting Connections in Wikipedia

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Learning to Find Interesting Connections in Wikipedia - scientific work related to Wikipedia quality published in 2010, written by Marek Ciglan, Etienne Rivière and Kjetil Nørvåg.

Overview

To help users answer the question, what is the relation between (real world) entities or concepts, authors might need to go well beyond the borders of traditional information retrieval systems. In this paper, authors explore the possibility of exploiting the Wikipedia link graph as a knowledge base for finding interesting connections between two or more given concepts, described by Wikipedia articles.Authors use a modified Spreading Activation algorithm to identify connections between input concepts.The main challenge in approach lies in assessing the strength of a relation defined by a link between articles. Authors propose two approaches for link weighting and evaluate their results with a user evaluation. Authors results show a strong correlation between used weighting methods and user preferences; results indicate that the Wikipedia link graph can be used as valuable semantic resource.

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