Parth Parikh, Mrunank Mistry, Dhruvam Kothari, S. Khachane
{"title":"光谱绽放过滤器的客户端搜索","authors":"Parth Parikh, Mrunank Mistry, Dhruvam Kothari, S. Khachane","doi":"10.1109/IEMCON51383.2020.9284946","DOIUrl":null,"url":null,"abstract":"A Bloom filter is a space-efficient probabilistic data structure that allows for set membership queries with some degree of false positives. In this paper, we propose a technique to add search functionality using a variant of Bloom filters - Spectral Bloom filters. Apart from being space-efficient, our proposed solution produces results comparable to search techniques such as Inverted Index and is a strong candidate for client-side searching.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"31 1","pages":"0867-0875"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spectral Bloom Filters for Client Side Search\",\"authors\":\"Parth Parikh, Mrunank Mistry, Dhruvam Kothari, S. Khachane\",\"doi\":\"10.1109/IEMCON51383.2020.9284946\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Bloom filter is a space-efficient probabilistic data structure that allows for set membership queries with some degree of false positives. In this paper, we propose a technique to add search functionality using a variant of Bloom filters - Spectral Bloom filters. Apart from being space-efficient, our proposed solution produces results comparable to search techniques such as Inverted Index and is a strong candidate for client-side searching.\",\"PeriodicalId\":6871,\"journal\":{\"name\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"volume\":\"31 1\",\"pages\":\"0867-0875\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMCON51383.2020.9284946\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMCON51383.2020.9284946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Bloom filter is a space-efficient probabilistic data structure that allows for set membership queries with some degree of false positives. In this paper, we propose a technique to add search functionality using a variant of Bloom filters - Spectral Bloom filters. Apart from being space-efficient, our proposed solution produces results comparable to search techniques such as Inverted Index and is a strong candidate for client-side searching.
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