[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Sun et al., 2022 - Google Patents

An Ordered Semantic Clustering Algorithm Supporting Urban Block Knowledge Graph

Sun et al., 2022

Document ID
4980671329103865548
Author
Sun H
Chen J
Liu J
Publication year
Publication venue
2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs)

External Links

Snippet

City is a unified organism, the use function of different land use reasonably organize the parts together, should not only meet the relationship between each other, also want to avoid the bad influence and interference between each other, the city's financial and trade, public …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30946—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
    • G06F17/30961—Trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30994—Browsing or visualization
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587—Details of specialised database models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30312—Storage and indexing structures; Management thereof
    • G06F17/30321—Indexing structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30241—Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99941—Database schema or data structure
    • Y10S707/99948—Application of database or data structure, e.g. distributed, multimedia, or image
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/28—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network with correlation of data from several navigational instruments
    • G01C21/30—Map- or contour-matching
    • G01C21/32—Structuring or formatting of map data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99941—Database schema or data structure
    • Y10S707/99943—Generating database or data structure, e.g. via user interface
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Hu et al. Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach
CN115269751B (en) Method for constructing geographic entity space-time knowledge graph ontology library
Hong et al. Hierarchical community detection and functional area identification with OSM roads and complex graph theory
Hu et al. A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data
Laurini et al. Fundamentals of spatial information systems
Worboys Modeling indoor space
Xie The overlaid network algorithms for areal interpolation problem
Gao et al. Towards Platial Joins and Buffers in Place-Based GIS
CN114238542A (en) Multi-level real-time fusion updating method for multi-source traffic GIS road network
Mete Geospatial big data analytics for sustainable smart cities
Huang et al. Mining crowdsourced trajectory and geo‐tagged data for spatial‐semantic road map construction
Wang et al. A graph-based visual query method for massive human trajectory data
Sun et al. An Ordered Semantic Clustering Algorithm Supporting Urban Block Knowledge Graph
Cai et al. Visual analysis of land use characteristics around urban rail transit stations
Zhao et al. Efficient semantic enrichment process for spatiotemporal trajectories
Trajcevski et al. Semantically augmented range queries over heterogeneous geospatial data
Chaudhry et al. Modelling geographic phenomena at multiple levels of detail
Richardson Advances in Spatial Data Handling: 10th International Symposium on Spatial Data Handling
Simumba et al. Spatially and semantically diverse points extraction using hierarchical clustering
Xu Multi-attribute Trajectory Data Management
Jiang et al. Exploring the spatiotemporal characteristics of intracity travels by time series clustering: A case study of Beijing
Piekenbrock et al. Intrinsic point of interest discovery from trajectory data
Yao et al. A spatio-temporal geocoding model for vector data integration
Tveite Data modeling and database requirements for geographical data
He et al. Construction of semantic annotation framework for stacked trajectory model