It’s well known that Federated Searching and Local Indexed Searching each offer strengths and weaknesses when it comes to powering the content discovery process. Federated Searching provides breadth of content coverage and real-time results from the many sources searched, yet can yield slower performance and inconsistent results. Indexed Searching brings speed and precision to queries against its local repository, yet can be incomplete and out-of-date in its coverage.
Muse® Hybrid brings the best of both approaches combined, without the drawbacks of either. By merging the powerful Muse Search environment with a high performance local indexed search engine, Muse® Hybrid allows users to search across remote and local resources at the same time, and retrieve current, complete results in less time and with more accuracy.
The Local Indexed Search is based on Muse® Central Index, which is a metadata repository that can index e-book and article metadata, catalog records, and other information harvested from institutional repositories and other digital collections. The main components of Muse Central Index are the Storage, which keeps all records available in Muse Central Index, and the Index.
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