A technique for measuring the relative size and overlap of public Web search engines
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Discovering the representative of a search engine
Proceedings of the tenth international conference on Information and knowledge management
Capturing collection size for distributed non-cooperative retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating sampling methods for uncooperative collections
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Ranking bias in deep web size estimation using capture recapture method
Data & Knowledge Engineering
Foundations and Trends in Information Retrieval
Size estimation of non-cooperative data collections
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
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Algorithms in distributed information retrieval often rely on accurate knowledge of the size of a collection. The "multiple capture-recapture" method of Shokouhi et al. is one of the more reliable algorithms for determining collection size, but it relies on samples with a uniform number of documents. Such uniform samples are often hard to obtain in a working system. A simple generalisation of multiple capture-recapture does not rely on uniform sample sizes. Simulations show it is as accurate as the original method even when sample sizes vary considerably, making it a useful technique in real tools.