Detailed Information on Publication Record
2017
Popularity-Based Ranking for Fast Approximate kNN Search
ANTOL, Matej and Vlastislav DOHNALBasic information
Original name
Popularity-Based Ranking for Fast Approximate kNN Search
Authors
ANTOL, Matej (703 Slovakia, belonging to the institution) and Vlastislav DOHNAL (203 Czech Republic, guarantor, belonging to the institution)
Edition
Informatica, Lithuanian Academy of Sciences, 2017, 0868-4952
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Netherlands
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 1.386
RIV identification code
RIV/00216224:14330/17:00094704
Organization unit
Faculty of Informatics
UT WoS
000398983000001
Keywords in English
kNN query;approximate search;query popularity;index structure;metric space
Tags
International impact, Reviewed
Změněno: 29/6/2020 12:54, doc. RNDr. Vlastislav Dohnal, Ph.D.
Abstract
V originále
Similarity searching has become widely available in many on-line archives of multimedia data. Users accessing such systems look for data items similar to their specific query object and typically refine results by re-running the search with a query from the results. We study this issue and propose a mechanism of approximate kNN query evaluation that incorporates statistics of accessing index data partitions. Apart from the distance between database objects, it also considers the prior query answers to prioritize index partitions containing frequently retrieved data, so evaluating repetitive similar queries more efficiently. We verify this concept in a number of experiments.
Links
| GA16-18889S, research and development project |
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