Federated Search in the Wild

The Combined Power of over a Hundred Search Engines

by Dong Nguyen, Thomas Demeester (Ghent University), Dolf Trieschnigg, and Djoerd Hiemstra

Federated search has the potential of improving web search: the user becomes less dependent on a single search provider and parts of the deep web become available through a unified interface, leading to a wider variety in the retrieved search results. However, a publicly available dataset for federated search reflecting an actual web environment has been absent. As a result, it has been difficult to assess whether proposed systems are suitable for the web setting. We introduce a new test collection containing the results from more than a hundred actual search engines, ranging from large general web search engines such as Google and Bing to small domain-specific engines. We discuss the design and analyze the effect of several sampling methods. For a set of test queries, we collected relevance judgments for the top 10 results of each search engine. The dataset is publicly available and is useful for researchers interested in resource selection for web search collections, result merging and size estimation of uncooperative resources.

to be presented at the The 21st ACM International Conference on Information and Knowledge Management, CIKM 2012.

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