Retrieval Of Geographic Information Research Articles

A machine learning approach to extracting spatial information from geological texts in Chinese

Texts have become an important spatial data resource. Interpretation of unstructured geoscience texts using natural language processing methods can effectively facilitate the discovery and retrieval of geographic information. Yet studies on the extraction of spatial information from textual geoscience data are limited compared to digital geoscience data. In this work, a machine learning approach is proposed for mining spatial relations in Chinese geological texts. The approach views spatial relation extraction as a sequence labeling problem, avoids the division of relation categories, and enables mining fine-grained spatial relations. The extracted geological texts commonly describe three-dimensional spatial relations among regions, strata, and lithologies. The extracted spatial relations are classified into three major categories (topological relations, absolute directional relations and relative directional relations) and 14 subcategories. We validated the proposed model with a test dataset, constructed visual displays of the extracted spatial relations on different topics, and quantified the uncertainty in the process from spatial entity recognition to spatial relation extraction. With the detailed portrayal of these spatial relations, this study provides support for solving theoretical and practical problems of cognition, prediction, decision-making, and evaluation in geoscience.

Retraction Note: Image detection of mountain soil loss and human avoidance trajectory based on cloud computing and machine learning

With the continuous progress and development of modern social science management and network security technology in China, the wide application of new-generation technologies such as intelligent robotics learning has made it more and more extensive in the field of analysis. At present, it has fully played an important technical leading role in many application fields, such as analysis methods, collection and sorting ability, analysis of various large-scale business computing application statistical data of enterprises, mining theoretical knowledge of natural environment science, image recognition, retrieval of global geographic location information and so on. Through the simulation of soil erosion in mountainous areas in my country, dynamic data analysis describes the basic situation of soil erosion in various mountainous areas in my country and the whole process of its evolution and development and comprehensively analyzes and studies various soil erosion events in mountainous areas in my country. The corresponding solutions can effectively and accurately respond to emergencies of soil erosion in mountainous areas and effectively reduce the loss of soil and water crops and economic losses in natural disasters. In recent years, information technology companies related to computer and machine learning capabilities, especially based on machine cloud computing, learning science and technology based on the theory of human machine artificial intelligence, and combining related professional technologies, have been used in various areas to prevent floods, droughts, risks, and rain in various areas. Disaster reduction and other non-natural engineering construction technology prevention measures have gradually been applied. The main research question of this paper is to design a related human body trajectory image detection system for new human facial image processing based on machine learning, and information collection and detection management system, and conduct in-depth research on its application prospects.

A Rule‐Based Strategy for the Semantic Annotation of Geodata

AbstractThe ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. This ability will enhance discovery, retrieval and translation of geographic information as well as the reuse of geographic information in different contexts. The problem of generating semantic annotations has been recognized as one of the most serious obstacles for realizing the Geospatial Semantic Web vision. We present a rule‐based strategy for the semantic annotation of geodata that combines Semantic Web and Geospatial Web Services technology. In our approach, rules are employed to partially automate the annotation process. Rules define conditions for identifying geospatial concepts. Based on these rules, spatial analysis procedures are implemented that allow for inferring whether or not a feature in a dataset represents an instance of a geospatial concept. This automated evaluation of features in the dataset generates valuable information for the creation and refinement of semantic annotations on the concept level. The approach is illustrated by a case study on annotating data sources containing representations of lowlands. The presented strategy lays the foundations for the specification of a semantic annotation tool for geospatial web services that supports data providers in annotating their sources according to multiple domain views.

A multi-Agent system architecture for geographic information gathering

World Wide Web (WWW) is a vast repository of information, including a great deal of geographic information. But the location and retrieval of geographic information will require a significant amount of time and effort. In addition, different users usually have different views and interests in the same information. To resolve such problems, this paper first proposed a model of geographic information gathering based on multi-Agent (MA) architecture. Then based on this model, we construct a prototype system with GML (Geography Markup Language). This system consists of three tiers-Client, Web Server and Data Resource. Finally, we expatiate on the process of Web Server.

Geographic Information Retrieval and the World Wide Web: A Match Made in Electronic Space

This article looks at the access to geographic information through a review of information science theory and its application to the WWW. The two most common retrieval systems are information and data retrieval. A retrieval system has seven elements: retrieval models, indexing, match and retrieval, relevance, order, query languages and query specification. The goal of information retrieval is to match the user's needs to the information that is in the system. Retrieval of geographic information is a combination of both information and data retrieval. Aids to effective retrieval of geographic information are: query languages that employ icons and natural language, automatic indexing of geographic information, and standardization of geographic information. One area that has seen an explosion of geographic information retrieval systems (GIR's) is the World Wide Web (WWW). The final section of this article discusses how seven WWW GIR's solve the the problem of matching the user's information needs to the information in the system.

Interactive Graphics in Data Processing: Geometric relationships for retrieval of geographic information

Reported is an experimental technique that has been developed for retrieving, by geometrical means, information related to city maps. This paper emphasizes the analysis needed to translate a retrieval query into relationships among points, vectors, and polygons. An illustration of the technique is given.