NDLI: Multi-Granularity Locality-Sensitive Bloom Filter

Content Provider	IEEE Xplore Digital Library
Author	Jiangbo Qian Qiang Zhu Huahui Chen
Copyright Year	1968
Abstract	In many applications, such as homeland security, image processing, social network, and bioinformatics, it is often required to support an approximate membership query (AMQ) to answer a question like “is an (query) object q near to at least one of the objects in the given data set Ω?” However, existing techniques for processing AMQs require a key parameter, i.e., the distance value, to be defined in advance for the query processing. In this paper, we propose a novel filter, called multi-granularity locality-sensitive Bloom filter (MLBF), which can process AMQs with multiple distance granularities. Specifically, the MLBF is composed of two Bloom filters (BF), one is called basic multi-granularity locality-sensitive BF (BMLBF), and the other is called multi-granularity verification BF (MVBF). The BMLBF is used to store the data objects. It adopts an alignable locality-sensitive hashing (LSH) function family to support multiple granularities. The MVBF is used to reduce the false positive rate of the MLBF. The false negative rate of the MLBF is reduced by applying AND-constructions followed by an OR-construction. In addition, based on the MLBF structure, we suggest a more spaceeffective variant, called the MLBF , to further reduce space cost. Theoretical analyses for estimating false positive/negative rates of the MLBF/MLBF are given. Experiments using synthetic and real data show that the theoretical estimates are quite accurate, and the MLBF/MLBF technique can handle AMQs with low false positive and negative rates for multiple distance granularities.
Sponsorship	IEEE Computer Society Technical Committee on Distributed Process IEEE Computer Society Technical Committee on VLSI IEEE Technical Committee on Computer Architecture IEEE Computer Society
Starting Page	3500
Ending Page	3514
Page Count	15
File Size	2153098
File Format	PDF
ISSN	00189340
Volume Number	64
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Social network services US Department of Homeland Security Gaussian distribution Security Bioinformatics Query processing Informatics false positive/negative rates approximate membership query query processing Bloom filter locality-sensitive hashing Approximate membership query
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Software Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Locality-Sensitive Bloom Filter for Approximate Membership Query

Generalized Bloom Filters

Big data query optimization by using Locality Sensitive Bloom Filter

Weighted bloom filter.

False negative problem of counting Bloom filter

Adaptive bloom filter.

An Improved Construction for Counting Bloom Filters (2006)

Rank-indexed hashing: A compact construction of bloom filters and extra bits per counter (σ) lg(M/N

Bloom Filter Accelerator for String Matching, in

Multi-Granularity Locality-Sensitive Bloom Filter

Similar Documents

Locality-Sensitive Bloom Filter for Approximate Membership Query

Generalized Bloom Filters

Big data query optimization by using Locality Sensitive Bloom Filter

Weighted bloom filter.

False negative problem of counting Bloom filter

Adaptive bloom filter.

An Improved Construction for Counting Bloom Filters (2006)

Rank-indexed hashing: A compact construction of bloom filters and extra bits per counter (σ) lg(M/N

Bloom Filter Accelerator for String Matching, in

Multi-Granularity Locality-Sensitive Bloom Filter