179 results about "Geographic entity" patented technology

Methods, systems and processor-readable media for extracting and classifying location information utilizing social media messages and/or data thereof. The social media messages can be sampled from a social media database and the messages filtered based on a heuristic rule. A geolocation entity from the unstructured social media messages can be extracted utilizing a geolocation entity extracting module. The messages with the geoentities can be uploaded onto a crowd sourcing platform to manually annotate the messages with a label. A text classification model can be built and learned from the label utilizing a machine learning algorithm and the messages can be classified by a location classifier in order to extract the user location. The user location can then be transformed into a geocode so that a spatial search can be enabled and the distance between the locations can be easily calculated.

The invention discloses a spatiotemporal database management method, as well as a management system and a program product thereof. The spatiotemporal database management system comprises a data collection part, a spatiotemporal data association part and a spatiotemporal data management part, wherein, the data collection part is used to collect or receive the spatial information and the timing information about a geographical entity from external systems, and the produced and existed object timing information of the data are arranged; the spatiotemporal data association part is used to associate various data obtained from the data collection part with the object timing information, and store the association into a corresponding spatiotemporal data file, so as to express the evolution history of the geographical entity and predict the change of the geographical entity; the spatiotemporal data management part is used to respectively store the spatiotemporal data file produced by the spatiotemporal data association part according to the temporal information recorded by the timing information of the geographical entity and the evolution trend recorded by the spatial information of the geographical entity, so as to compose a spatiotemporal database.

User locality information can be used to improve various aspects of search results pages. Queries can be suggested based on the user location while excluding common query suggestions that involve an unrelated geographic entity. Deeplinks can also be modified to include location based suggestions. Additionally, results for specialized searches such as travel searches can be improved by employing user locality information.

The invention discloses a multi-source heterogeneous multi-attribute POI (point of interest) integration method. The multi-source heterogeneous multi-attribute POI integration method includes firstly acquiring data sets to be integrated from POI data sources A and B, and deweighting two heterogeneous-attribute data sets respectively; browsing each POI in the two data sets respectively and calculating similarity of each attribute of the POI to obtain an attribute similarity matrix on the premise that the attribute similarity calculation rule is obeyed; solving a weighted multi-attribute POI similarity vector; calculating the maximum value Max of various components in the POI similarity vector and comparing the Max with a threshold value T; adding different attribute items of the POI standing for the same geographic entity and integrating the same attribute items of the same value. According to overall importance and different influence degrees of the attributes, various types of attributes of the POI are considered differently, so that the method better lives up to actual operation of POI integration, and accuracy and efficiency of automatic POI integration can be remarkably improved.

Various embodiments present a combined visual entity that represents overlapping visual entities. The combined visual entity can include a primary visualization that represents one of the overlapping visual entities and annotations that represent others of the overlapping visual entities. For example, a map view can include multiple geographical entities that overlap. A primary visualization can be rendered that represents one of the multiple geographical entities. The primary visualization can be visually annotated (e.g., with symbols, letters, or other visual indicators) to indicate others of the multiple geographical entities. In some embodiments, a zoom operation can cause visual entities to be added and/or removed from the combined visual entity.

The invention relates to an electric power facility computer manage software, namely a power distribution productive management information figure system. The figure system sets a compare geographic entity and a geographical position layer special for existing power distribution network and power distribution facility, establishes five relative figure data modules according with existing management mode, compiles graphics drawing, automatic generating and linkage program. Data in each figure is interrelated, and one data is changed that can realize a plurality of figure data linkage and awoke. The figure system can reflect condition of the power distribution network and facility timely and accurately, particularly a plurality of figure linkage function that can save mass labour resource, increase information instantaneity and reliability, avoid abuse of differ manage information to the figure and easy to oversight, accordingly, provides an advanced computer manage special software to the power distribution productive department. The manage software provided by the invention has important significance for ensuring correctness of power distribution productive commanding and decision-making, realizing scientification and standardization of power distribution productive manage, increasing emergency ability and working efficiency.

The invention discloses a multi-dimensional geographic scene identification method fusing geographic region knowledge. The method comprises the steps of preprocessing images in a database to obtain satisfied geographic scene images; obtaining object region image blocks by utilizing a method for quickly searching for object regions in the images; pre-training the obtained object region image blocks of the geographic images by using a deep convolutional neural network, performing an accurate adjustment process until the performance of the deep convolutional neural network of the scene images is no longer improved, and fusing feature matrixes into output eigenvectors; pre-establishing a geographic entity noun keyword dictionary by acquired entity noun data in geographic scene classification, performing word segmentation on target identification result data to obtain key words in a target identification result, and establishing text features; and fusing the text features and multi-dimensional image features into eigenvectors as inputs, realizing cross-media-data identification classification, and realizing scene classification fusing geographic entity information.

The invention discloses a point group geographic entity selection method under the restriction of correlated elements. The method comprises the following steps of: 1) maintaining the contour form of a point-like geographic element group; 2) maintaining the density distribution characteristics of the point group, clustering the point elements according to the density, and sorting and selecting; and 3) restricting correlated elements. By the method, a map needed by a user can be obtained rapidly and effectively. The aesthetic quality of the map is ensured and the prominence is given to the key points for easy query analysis while strengthening the essence, abandoning the refuse and maintaining the logical relation and solitary relation between the map objects by analyzing the requirements of the user.

The invention provides an SPH (smoothed particle hydrodynamics) algorithm-based simulation method and an SPH (smoothed particle hydrodynamics) algorithm-based simulation system of the process of breaking dam by flood. The simulation method comprises the following steps: A. acquiring on-site geographic spatial information data; B. establishing a dynamical model of the process of breaking dam by flood based on the geographic spatial information data obtained in the step A; C. establishing a geographic entity model according to the geographic spatial information data obtained in the step A; D. analyzing the dynamical model obtained in the step B into an SPH calculation method; E. initializing the geographic entity model obtained in the step C to be hydrodynamics particles and boundary particles for the SPH calculation; F. circularly calculating based on the SPH algorithm; G. carrying out the spatial-temporal process modeling on the calculated value result obtained in the step F to obtain a 3D spatial-temporal model and a database of the process of breaking the dam by flood; and H. dynamically visualizing the 3D spatial-temporal model and the database of the process of breaking dam by flood obtained in the step G. By using the SPH method in the geographic process simulation, the authenticity of the simulation result is effectively improved.

The invention discloses a method for extracting a relationship among geographic entities contained in an internet text. The method comprises the following steps of data preprocessing, document vectorization, weight calculation, keyword extraction and relational tuple construction. The method specifically comprises the steps of inputting the network text containing the geometric entities, extracting the spatial relationship or the semantic relationship among the geometric entities through data preprocessing, and obtaining a webpage pure text and candidate keywords; performing vectorization on the text by adopting a word-level vector space model, and establishing a word-context matrix; designing a novel weight calculation method for performing weight calculation on the geometric entities; and selecting the word with the maximum weight as a keyword from a context vector, constructing a relational tuple, and finally finishing geometric entity extraction. According to the method, a semantic-based retrieval mode is provided, so that a conventional search technology depending on the keyword is changed; and on the premise of lack of large-scale tagged corpora and a geometric knowledge library, geometric relationship description words can be quickly extracted, so that the operation efficiency is improved and the labor cost is greatly reduced.

The invention discloses a POI (Point of interest) and remote-sensing image integrated urban function zone division method. The method comprises the following steps of (1), obtaining POI data, remote-sensing images and space geographic entity data of a region; (2), selecting classes sensitive to urban function zone division from class attributes of the POI data, thereby forming evaluation classes,forming function POI data based on the POI data corresponding to the evaluation classes, matching the function POI data with the space geographic entity data, thereby obtaining an initial distributionstructure of each class of POI data in each geographic entity; (3), extracting land cover data from the remote-sensing images of the region; (4), making a decision tree classification rule based on the initial distribution structure of each class of POI data in the (2) and the land cover data in the (3); and (5), dividing urban function zones of the region according to the decision tree classification rule. According to the method, on the basis of a decision tree classification algorithm, the POI data and Landsat remote-sensing data are combined, so the urban function zones are rapidly divided.

The system can realize the functions of semantic search, multi-dimensional query, association analysis, knowledge reasoning and the like of geographic knowledge, can realize service data self-defined hitching and IoT sensing information dynamic hitching in geographic entity structured management, and realizes multi-source heterogeneous data fusion. The multi-source heterogeneous data fusion method for providing scientific decision support for intelligent construction comprises the steps of extracting a geographic entity space-time knowledge graph, and performing knowledge merging on the extracted geographic entity space-time knowledge graph and a plurality of external knowledge graphs to form a complete geographic knowledge graph.

The invention relates to a land use zoning method giving consideration to geographic entity semantic similarity. The land use zoning method includes inputting a basic land use zone database, iterating and extracting small picture spots and sequencing the picture spots, partitioning modes of the small picture spots and integrating in consideration of the geographic entity semantic similarity, determining land use zones according to a land use zoning method after semantic change value integrated is minimum, extracting boundary lines of the integrated picture spots and generating land use zoning pictures. Geographic entity semantic similarity is sufficiently utilized, the efficient and automatic land use zoning method is formed and scientificity, rationality and operability of land use zoning are improved.

The embodiment of the invention discloses an address information analysis method, device and system and a data acquisition method. The address information analysis method comprises the steps of obtaining to-be-analyzed address information in original data; extracting features of the to-be-analyzed address information by using a natural language processing technology, selecting the extracted features, and vectorizing the selected features to obtain feature vectors; inputting the feature vectors into a preset model to obtain an initial array comprising a geographic entity and an administrative division level corresponding to the geographic entity; according to administrative division levels, carrying out sorting and duplicate removal on the geographic entities in the initial array to obtaina standard array; and encoding the standard array to obtain a geocoding result. The geographic entity and administrative division of the address information are recognized based on the model, a rule base does not need to be built, and occupied resources are few. The prediction model is optimized through a feature selection algorithm, so that the prediction accuracy and the calculation rate are improved.

The invention relates to the technical field of data processing, in particular to a method for analyzing spatial and temporal distribution of population based on big data. The method accurately positions the dwell location and dwell time of a mobile phone by using the mobile phone's motion track and combining the location of the mobile phone connected to a base station. Since the mobile phone userbrings the mobile phone to the body in real time, the mobile phone is accurately positioned, that is the same as precise positioning of the mobile phone user. After the positioning, by determining the specific geographic entity in which each mobile phone user resides in each time period, counting the population dwell data of each geographic entity in each time period, and summarizing the counteddwell data of each geographic entity, the population dwell data in any time period in any area can be obtained.

Methods, apparatus, and techniques for provisioning geofences are disclosed. In one aspect, a map comprising one or more selectable geographic entities is displayed. In response to a selection by a user of at least one geographic entity of the one or more geographic entities, a geofence corresponding to the selected at least one geographic entity is created. In another aspect, a user may provide an input including one or more keywords. In response to determining that a first geographic entity has attributes that match the one or more keywords, a geofence corresponding to the first geographic entity is created.

Provided are systems, methods, and computer-readable media for determining locations of interest to a user. User activity over a period of time is obtained and used to determine geographic entities (e.g., locations) of interest. The user activity is aggregated by geographic entity and a relevancy score is calculated for each geographic entity. The geographic entity having the highest score is stored as a location of interest in a location profile for the user. Multiple geographic entities having the highest specified number of relevancy scores may also be stored.

The invention discloses a method for subtly organizing regular geographic entity space geometry data. Firstly, geometrical information of a regular geographic entity and parts of the regular geographic entity is collected, secondly the regular geographic entity and the parts of the regular geographic entity are abstracted and simplified, then feature points are extracted, a regular geographic entity area triangular facet network is built, namely the initial triangular facet network is built in a regular geographic entity area, the shape and the size of a triangular facet depends on the densities and positions of the feature points, and finally the triangular facet network is optimized to complete the Delaunay triangular facet network. The method for subtly organizing the regular geographic entity space geometry data has the advantages that a regular geographic entity space geometry structure is subtly expressed, the interior of the geographic entity is made to have the description of space topological relation, and a feasible method is provided for solving subtle analysis problems such as subtle organizing of the smart city regular geographic entity space geometry data and an interior optimal path analysis.

Systems, devices, features, and methods for collecting or storing data corresponding to disputed territories for a geographic database, such as for use with a navigation system, are disclosed. For example, one method comprises identifying a data record that represents a geographic feature of a disputed area. An indication of dispute may be assigned to the identified data record, in which the indication of dispute represents that the identified data record corresponds to a feature in dispute between multiple geographic entities. Another data record that represents a geographic feature in dispute may also be identified. The indication of dispute and/or the data records of the features may be stored in a geographic database.

The invention discloses a three-dimensional geographic information acquisition system. The system comprises a geographic information public server-side and a mobile measurement terminal; the geographic information public server-side provides the support for a mobile measurement terminal, is responsible for receiving picture and posture information acquired by the terminal to perform the construction and update operation of a three-dimensional model; the mobile measurement terminal is responsible for receiving and displaying the three-dimensional landscape data transmitted by the cloud side, an enhanced realistic display way is used for performing fusion display; and meanwhile, the factor-oriented geographic entity three-dimensional information acquisition work can be performed based on the terminal multisensory. The system realizes the fast, low-cost and efficient update of the disperse geographic entity change, effectively reduces the acquisition cost of the multi-dimension geographic information, can be directly applied to the field classification and quality inspection of the basic surveying, can realize the indoor work and field integrated novel production mode of the multi-dimension geographic information acquisition, the fast update efficiency and quality of the disperse geographic entity change data are promoted, and the application demand on the geographic information by the big data era is satisfied.

The invention relates to a GraphDB-based space-time knowledge graph construction method and device, a medium and equipment. The method comprises the following steps: fusing an OGC standard to construct an architecture of a geographic entity; extracting data related to the geographic entity in the spatio-temporal data to generate an individual knowledge set of the target object; and storing the individual knowledge set into a GraphDB database to form a space-time knowledge graph. Accurate ground object information contained in multi-temporal and large-range remote sensing images is organized and fused, space-time information is described comprehensively and meticulously, and inference rules are introduced to overcome the defects of OWL in inference ability, so that the knowledge graph has stronger inference ability.