Spreading Activation for Web Scale Reasoning: Promise and Problems

Nazihah Md. Akim, Alan Dix, Akrivi Katifori, Giorgos Lepouras, Nadeem Shabir, Costas Vassilakis
ACM WebSci 11, poster presentation

Abstract:
Various forms of spreading activation has been used in a number of web systems, not least in the PageRank algorithm. In our own work we have been using this as a technique for managing context over small and large ontologies, and both our own work and that in LarKC suggests that spreading activation has the potential to aid in reasoning over web-scale data sets including the growing set of linked open data resources. Of particular importance is that spreading activation can be applied locally to a dynamic self-selecting working set of an (practically) unbound linked data collection, as well as globally to the entire collection. However, this potential does not come without problems, some concerning the nature of the algorithm on any large data set, and some more to do with the particular nature of linked open data.

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