
To help users answer the question, what is the relation between (real world) entities or concepts, we might need to go well beyond the borders of traditional information retrieval systems. In this paper, we 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.We use a modified Spreading Activation algorithm to identify connections between input concepts.The main challenge in our approach lies in assessing the strength of a relation defined by a link between articles. We propose two approaches for link weighting and evaluate their results with a user evaluation. Our 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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
