Show simple item record

dc.contributor.authorSalem, Kenen_US
dc.date.accessioned2004-05-31T22:23:46Z
dc.date.available2004-05-31T22:23:46Z
dc.date.created1993-08en_US
dc.date.issued1998-10-15en_US
dc.identifier.urihttp://hdl.handle.net/1903/593
dc.description.abstractThis paper is concerned with the problem of identifying names which occur frequently in an ordered list of names. Such names are called hot spots. Hot spots can be identified easily by counting the occurrences of each name and then selecting those with large counts. However, this simple solution requires space proportional to the number of names that occur in the list. In this paper, we present and evaluate two hot spot estimation techniques. These techniques guess the frequently occurring names, while using less space than the simple solution. We have implemented and tested both techniques using several types of input traces. Our experiments show that very accurate guesses can be made using much less space than the simple solution would require. (Also cross-referenced as UMIACS-TR-93-74)en_US
dc.format.extent301699 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3115en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-93-74en_US
dc.titleSpace-Efficient Hot Spot Estimationen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record