JEDI: These aren't the JSON documents you're looking for...
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00365165" target="_blank" >RIV/68407700:21240/22:00365165 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1145/3514221.3517850" target="_blank" >https://doi.org/10.1145/3514221.3517850</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3514221.3517850" target="_blank" >10.1145/3514221.3517850</a>
Alternative languages
Result language
angličtina
Original language name
JEDI: These aren't the JSON documents you're looking for...
Original language description
The JavaScript Object Notation (JSON) is a popular data format used in document stores to natively support semi-structured data. In this paper, we address the problem of JSON similarity lookup queries: given a query document and a distance threshold ????, retrieve all documents that are within ???? from the query document. Different from other hierarchical formats such as XML, JSON supports both ordered and unordered sibling collections within a single document which poses a new challenge to the tree model and distance computation. We propose JSON tree, a lossless tree representation of JSON documents, and define the JSON Edit Distance (JEDI), the first edit-based distance measure for JSON. We develop QuickJEDI, an algorithm that computes JEDI by leveraging a new technique to prune expensive sibling matchings. It outperforms a baseline algorithm by an order of magnitude in runtime. To boost the performance of JSON similarity queries, we introduce an index called JSIM and an effective upper bound based on tree sorting. Our upper bound algorithm runs in ???? (????????) time and ???? (???? +???? log ????) space, which substantially improves the previous best bound of ???? (????2) time and ???? (???? log ????) space (where ???? is the tree size). Our experimental evaluation shows that our solution scales to databases with millions of documents and JSON trees with tens of thousands of nodes.
Czech name
—
Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000421" target="_blank" >EF15_003/0000421: Big Code: Scalable Analysis of Massive Code Bases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data
ISBN
978-1-4503-9249-5
ISSN
0730-8078
e-ISSN
—
Number of pages
14
Pages from-to
1584-1597
Publisher name
Association for Computing Machinery
Place of publication
New York
Event location
Philadelphia
Event date
Jun 12, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000852705400115