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Discovering Interesting Subpaths with Statistical Significance from Spatiotemporal Datasets

ACM Transactions on Intelligent Systems and Technology(2020)10.1145/3354189Source: DataRank Database

Discovering Interesting Subpaths with Statistical Significance from Spatiotemporal Datasets is a research paper published in ACM Transactions on Intelligent Systems and Technology (2020). On theSindex it has a DataRank of 0. It has been cited 8 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access8 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (15 grants)Impact (FWCI 0.73)OA: bronzeTopics (18)IDs (PubMed, OpenAlex)SDGs (3)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (3)

Xun Zhou ORCID,Shashi Shekhar ORCID,Yiqun Xie ORCID

Live enrichment

PubMed:26657633 OpenAlex:https://openalex.org/W3005686672

National Science Foundation

Grant: IIS-1566386,1737633,1541876, 1029711, IIS-1320580,09409818

National Institutes of Health

Grant: UL1 TR002494, KL2 TR002492, TL1 TR002493

U.S. Department of Agriculture

Grant: 2017-51181-27222

U.S. Department of Defense

Grant: HM1582-08-1-0017, HM0210-13-1-0005

Advanced Research Projects Agency - Energy

Grant: DE-AR0000795

National Institutes of Health

Grant: 1TL1TR002493-01

NRSA Training Core

National Science Foundation

Grant: 1737633

S&CC-IRG Track 1: Connecting the Smart-City Paradigm with a Sustainable Urban Infrastructure Systems Framework to Advance Equity in Communities

National Institutes of Health

Grant: 1KL2TR002492-01

Institutional Career Development Core

National Science Foundation

Grant: 1901099

III: Medium: Investigating Spatial-Temporal Informatics for Transportation Science

National Science Foundation

Grant: 1541876

FEW: A Workshop to Identify Interdisciplinary Data Science Approaches and Challenges to Enhance Understanding of Interactions of Food Systems and Water Systems

National Science Foundation

Grant: 1029711

Collaborative Research: Understanding Climate Change: A Data Driven Approach

National Science Foundation

Grant: 1320580

III: Small: Investigating Spatial Big Data for Next Generation Routing Services

National Science Foundation

Grant: 1218168

III: Small: Towards Spatial Database Management Systems for Flash Memory Storage

National Science Foundation

Grant: 0940818

DataNet Full Proposal: Terra Populus: A Global Population/Environment Data Network

National Institutes of Health

Grant: 3UL1TR002494-02S1

University of Minnesota Clinical and TranslationalmScience Institute (UMN CTSI)

FWCI

0.73

Citation Percentile

0.7%

Citation Trend

2020

2022

2023

2025

bronzeLicense: https://www.acm.org/publications/policies/copyright_policy#Background

journalhttps://dl.acm.org/doi/pdf/10.1145/3354189

publisherhttps://dl.acm.org/doi/pdf/10.1145/3354189

publisherhttps://dl.acm.org/doi/10.1145/3354189

journalhttps://doi.org/10.1145/3354189

https://dx.doi.org/10.1145/3354189

Fields of Study

Data Management and AlgorithmsData-Driven Disease SurveillanceTime Series Analysis and Forecasting0202 electrical engineering, electronic engineering, information engineering02 engineering and technology0101 mathematics01 natural sciences

Keywords

Computer sciencePruningPath (computing)Baseline (sea)Monte Carlo methodAlgorithmData miningArtificial intelligenceTheoretical computer scienceStatisticsMathematics

Sustainable Development Goals

SDG 11: 11. SustainabilitySDG 13: 13. Climate actionSDG 0: Sustainable cities and communities