Searching a File System using Inferred Semantic Links

We describe Eureka, a file system search engine that takes into account the inherent relationships among files in order to improve the rankings of search results. The key idea behind our approach is a simple, yet powerful framework that automatically infers semantic links among files and thus transforms the file system in a network of hyper-linked documents. Based on this model, we propose the FileRank metric that examines the structure of the semantic graph and essentially quantifies the “importance ” of each file in the file system. By combining FileRank with conventional IR metrics, Eureka can bias the rankings of the search results toward the more important files and thus provide more effective support in the task of locating useful files. We outline the design of the Eureka search engine and discuss the inference of semantic links and the computation of the FileRank metric