Temporal JSON Keyword Search

Author:

Dyreson Curtis1ORCID,Shatnawi Amani2ORCID,Bhowmick Sourav S.3ORCID,Sharma Vishal4ORCID

Affiliation:

1. Department of Computer Science, Utah State University, Logan, UT, USA

2. Department of Information Technology, Yarmouk University, Irbid, Jordan

3. College of Computing & Data Sc., Nanyang Technological University, Singapore, Singapore

4. Department of Heath Administration & Policy, University of Nevada, Las Vegas, Las Vegas, NV, USA

Abstract

JSON keyword search searches the current versions of documents in a collection. However, JSON documents change over time due to edits. Some applications, such as data forensics and auditing, need to search past versions of documents and for changes to documents. This paper introduces a system called Temporal JSON Keyword Search (TJKS) for search in a collection of JSON documents that vary over time. TJKS lets users control which temporal slice, or part of the history, can be searched using a temporal search semantics; we support both of the major temporal semantics: sequenced and nonsequenced search. This paper presents the semantics of temporal JSON keyword search, discusses an efficient implementation, and evaluates the implementation. Our extensions are largely orthogonal to specific keyword search techniques, so this research provides a blueprint for extending keyword search to include time and potentially other kinds of metadata.

Publisher

Association for Computing Machinery (ACM)

Reference72 articles.

1. [n. d.]. DB-Engines Ranking. https://db-engines.com/en/ranking. Accessed: 2023--10--10.

2. [n. d.]. JSONPath. https://github.com/json-path/JsonPath. Accessed: 2023--10--10.

3. Enabling generic keyword search over raw XML data

4. Maintaining knowledge about temporal intervals

5. Toshiyuki Amagasa Masatoshi Yoshikawa and Shunsuke Uemura. 2000. A Data Model for Temporal XML Documents. In DEXA. 334--344. https://doi.org/10.1007/3--540--44469--6_31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3