{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T13:12:14Z","timestamp":1698066734566},"reference-count":7,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2006,10,30]],"date-time":"2006-10-30T00:00:00Z","timestamp":1162166400000},"content-version":"vor","delay-in-days":6238,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Softw Pract Exp"],"published-print":{"date-parts":[[1989,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This article presents a procedure for constructing a near\u2010perfect hashing function. The procedure, which is a modification of Cichelli's algorithm, builds the near\u2010perfect hashing function sufficiently fast to allow larger word sets to be used than were previously possible. The improved procedure is the result of examining the original algorithm for the causes of its sluggish performance and then modifying them. In doing so an attempt was made to preserve the basic simplicity of th original algorithm. The improved performance comes at the expense of more storage. The six modifications used to improve performance are explained in detail and experimental results are given for word sets of varying sizes.<\/jats:p>","DOI":"10.1002\/spe.4380191005","type":"journal-article","created":{"date-parts":[[2006,11,18]],"date-time":"2006-11-18T05:00:08Z","timestamp":1163826008000},"page":"967-978","source":"Crossref","is-referenced-by-count":11,"title":["Near\u2010perfect hashing of large word sets"],"prefix":"10.1002","volume":"19","author":[{"given":"Marshall D.","family":"Brain","sequence":"first","affiliation":[]},{"given":"Alan L.","family":"Tharp","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2006,10,30]]},"reference":[{"key":"e_1_2_1_2_2","volume-title":"File Organization and Processing","author":"Tharp Alan L.","year":"1988"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3532.3538"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/358808.358813"},{"key":"e_1_2_1_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/359863.359887"},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/358800.358806"},{"key":"e_1_2_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/358027.358051"},{"key":"e_1_2_1_8_2","doi-asserted-by":"crossref","unstructured":"KevinKarplusandGaryHaggard \u2018Finding minimal perfect hash functions\u2019 Proceedings of the Seventeenth ACM SIGCSE Technical Symposium February1986 pp.191\u2013193.","DOI":"10.1145\/953055.5899"}],"container-title":["Software: Practice and Experience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fspe.4380191005","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/spe.4380191005","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T19:13:55Z","timestamp":1698002035000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/spe.4380191005"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1989,10]]},"references-count":7,"journal-issue":{"issue":"10","published-print":{"date-parts":[[1989,10]]}},"alternative-id":["10.1002\/spe.4380191005"],"URL":"https:\/\/doi.org\/10.1002\/spe.4380191005","archive":["Portico"],"relation":{},"ISSN":["0038-0644","1097-024X"],"issn-type":[{"value":"0038-0644","type":"print"},{"value":"1097-024X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1989,10]]}}}