With increasing amount of data in deep web sources (hidden from general search engines behind web forms), accessing this data has gained more attention. In the algorithms applied for this purpose, it is the knowledge of a data source size that enables the algorithms to make accurate decisions in stopping crawling or sampling processes which can be so costly in some cases . The tendency to know the sizes of data sources is increased by the competition among businesses on the Web in which the data coverage is critical. In the context of quality assessment of search engines , search engine selection in the federated search engines, and in the resource/collection selection in the distributed search field , this information is also helpful. In addition, it can give an insight over some useful statistics for public sectors like governments. In any of these mentioned scenarios, in case of facing a non-cooperative collection which does not publish its information, the size has to be estimated . In this paper, the approaches in literature are categorized and reviewed. The most recent approaches are implemented and compared in a real environment. Finally, four methods based on the modification of the available techniques are introduced and evaluated. In one of the modifications, the estimations from other approaches could be improved ranging from 35 to 65 percent.
|Title of host publication||Proceedings of the 13th Dutch-Belgian Workshop on Information Retrieval, DIR 2013|
|Place of Publication||Aachen, Germany|
|Number of pages||2|
|Publication status||Published - 26 Apr 2013|
|Event||13th Dutch-Belgian Information Retrieval Workshop, DIR 2013 - Delft, Netherlands|
Duration: 26 Apr 2013 → 26 Apr 2013
Conference number: 13
|Name||CEUR Workshop Proceedings|
|Workshop||13th Dutch-Belgian Information Retrieval Workshop, DIR 2013|
|Period||26/04/13 → 26/04/13|
Khelghati, M., Hiemstra, D., & van Keulen, M. (2013). How much data resides in a web collection: how to estimate size of a web collection. In Proceedings of the 13th Dutch-Belgian Workshop on Information Retrieval, DIR 2013 (pp. 42-43). (CEUR Workshop Proceedings; Vol. 986). Aachen, Germany: CEUR.