Evaluation of a Dynamic Tree Structure for Indexing Query Regions on Streaming Geospatial Data

RHPTree—Risk Hierarchical Pattern Tree for Scalable Long Pattern Mining

ACM Transactions on Knowledge Discovery from Data ◽

10.1145/3488380 ◽

2022 ◽

Vol 16 (4) ◽

pp. 1-33

Author(s):

Danlu Liu ◽

Yu Li ◽

William Baskett ◽

Dan Lin ◽

Chi-Ren Shyu

Keyword(s):

High Performance ◽

Large Scale ◽

Pattern Mining ◽

Tree Structure ◽

Research Initiative ◽

Speed Up ◽

Dynamic Tree ◽

Significant Patterns ◽

Search Approach ◽

Hierarchical Pattern

Risk patterns are crucial in biomedical research and have served as an important factor in precision health and disease prevention. Despite recent development in parallel and high-performance computing, existing risk pattern mining methods still struggle with problems caused by large-scale datasets, such as redundant candidate generation, inability to discover long significant patterns, and prolonged post pattern filtering. In this article, we propose a novel dynamic tree structure, Risk Hierarchical Pattern Tree (RHPTree), and a top-down search method, RHPSearch, which are capable of efficiently analyzing a large volume of data and overcoming the limitations of previous works. The dynamic nature of the RHPTree avoids costly tree reconstruction for the iterative search process and dataset updates. We also introduce two specialized search methods, the extended target search (RHPSearch-TS) and the parallel search approach (RHPSearch-SD), to further speed up the retrieval of certain items of interest. Experiments on both UCI machine learning datasets and sampled datasets of the Simons Foundation Autism Research Initiative (SFARI)—Simon’s Simplex Collection (SSC) datasets demonstrate that our method is not only faster but also more effective in identifying comprehensive long risk patterns than existing works. Moreover, the proposed new tree structure is generic and applicable to other pattern mining problems.

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Interpretation of complex scenes using dynamic tree-structure Bayesian networks

Computer Vision and Image Understanding ◽

10.1016/j.cviu.2005.09.005 ◽

2007 ◽

Vol 106 (1) ◽

pp. 71-84 ◽

Cited By ~ 8

Author(s):

Sinisa Todorovic ◽

Michael C. Nechyba

Keyword(s):

Bayesian Networks ◽

Tree Structure ◽

Complex Scenes ◽

Dynamic Tree

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Multi-Robot Localization and Mapping Strategy: Utilizing Behavior Based Dynamic Tree Structure and Observer-explorer Routine

2007 IEEE International Conference on Automation Science and Engineering ◽

10.1109/coase.2007.4341721 ◽

2007 ◽

Author(s):

Kevin K. Leung ◽

Garratt Gallagher

Keyword(s):

Tree Structure ◽

Robot Localization ◽

Mapping Strategy ◽

Localization And Mapping ◽

Behavior Based ◽

Dynamic Tree ◽

Multi Robot

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Man-Computer Derivations of Tree Structure from Multivariate Data

PsycEXTRA Dataset ◽

10.1037/e473742008-109 ◽

1968 ◽

Author(s):

Gerald H. Shure ◽

Laurence I. Press ◽

Miles S. Rogers

Keyword(s):

Multivariate Data ◽

Tree Structure

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Building a tree structure

PsycEXTRA Dataset ◽

10.1037/e668292012-315 ◽

1976 ◽

Author(s):

Patricia Marks Greenfield ◽

Leslie Schneider

Keyword(s):

Tree Structure

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Web Based GIS Application using Open Source Software for Sharing Geospatial Data

International Journal of Advanced Remote Sensing and GIS ◽

10.23953/cloud.ijarsg.109 ◽

2015 ◽

Vol 4 (1) ◽

pp. 1224-1228 ◽

Cited By ~ 9

Author(s):

Debasish Chakraborty ◽

◽

Debanjan Sarkar ◽

Shubham Agarwal ◽

Dibyendu Dutta ◽

...

Keyword(s):

Open Source ◽

Open Source Software ◽

Geospatial Data ◽

Web Based ◽

Gis Application

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Using the potential of peripheral green areas of cities for educational and recreational purposes on the example of Stary Sącz, Nowy Targ and Kraków

Urban Development Issues ◽

10.2478/udi-2020-0005 ◽

2020 ◽

Vol 65 (1) ◽

pp. 53-63

Author(s):

Mateusz Kulig ◽

Anna Przeniczny ◽

Piotr Ogórek

Keyword(s):

Land Cover ◽

Environmental Protection ◽

Public Spaces ◽

Geospatial Data ◽

Valuable Resource ◽

Green Areas

AbstractGreen areas located on the peripheries of cities have the potential to become green public spaces not only of recreational but also educational character, promoting at the same time the knowledge about environmental protection. The cities included in the research belong to the małopolskie voivodeship (Lesser Poland voivodeship). With the use of geospatial data of land cover, as well as territorial forms of environmental protection, it was pointed that 48.4% of forest, wooded and shrub green areas located within city borders are covered by a form of environmental protection, thus being a valuable resource of significant nature potential. Making such spaces available in a conscious and attractive way is presented on the example of projects implemented in the cities of: Stary Sącz, Nowy Targ and Kraków. The presented projects were used to make recommendations for city authorities to create green public spaces.

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