The Web has become a major conduit to information repositories of all kinds. Web caches are employed to store web views to
provide an immediate response to recurring queries. However, the accuracy of the replicates in web caches encounters challenges
due to the dynamicity of web data. We are thus developing and evaluating a web caching system equipped with an efficient refresh
strategy. With the assistance of a novel index structure - the Aggregation Path Index (APIX), we built Argos, a web caching
system based on the GMD XQL query engine. Argos achieves a high degree of self-maintenance by diagnosing irrelevant data update
cases. It hence greatly improves the refresh performance of the materialized web view. We also report preliminary experimental
results assessing the performance of Argos compared to the state-of-the-art solution in the literature.
Keywords XQL Query Engine - Web Caching - View Maintenance - Indexing - XML - Data Update
This work was supported in part by several grants from NSF, namely, the NSF NYI grant #IRI 94-57609, the NSF CISE Instrumentation
grant #IRIS 97-29878, and the NSF grant #IIS 97-32897. Dr. Rundensteiner would like to thank our industrial sponsors, in particular,
IBM for the IBM partnership award. Li Chen would like to thank IBM for the IBM corporate fellowship.