Математические методы распознавания образов: Тезисы докладов 19-й Всероссийской конференции с международным участием
The rapid growth of geospatial data in the world enables the implementation of
data mining techniques to mine the patterns in geospatial data. In this paper the
authors have applied the algorithms that were previously used for mining slightly
changing patterns in time series to geospatial data of the real estate market. So the
paper discusses mining the patterns that slightly change in space (instead of time).
The paper uses data on the real estate market. The predicted variable (square
meter price) is analyzed respective to the district, distance to the city center, stations
of public transport, highways, shops, sports, entertainment, healthcare, education
centers, offices, parks etc. The proposed approach for mining slightly changing
patterns in geospatial data is highly applicable to any data with geo-tag, e.g. space
image recognition, geo-targeted marketing etc.
An array DBMS streamlines large N-d array management. A large portion of such arrays originates from the geospatial domain. The arrays often natively come as raster files while standalone command line tools are one of the most popular ways for processing these files. Decades of development and feedback resulted in numerous feature-rich, elaborate, free and quality-assured tools optimized mostly for a single machine. ChronosDB partially delegates in situ data processing to such tools and offers a formal N-d array data model to abstract from the files and the tools. ChronosDB readily provides a rich collection of array operations at scale and outperforms SciDB by up to 75× on average.
The Republic of Tatarstan is one of the most economically developed regions of Russia. Large-scale projects implemented in the republic make high demands for labor resource security. Understanding of the status and trends of the dynamics of labor resource potential of the Republic of Tatarstan will allow the region to build a competent management of key factors for future economic development. The article describes the results of investigation of the dynamics of labor resource potential of the Republic of Tatarstan. It highlights an attempt to use cartographic research method in combination with the geostatistical methods of analysis of statistical data on the population based on the current capabilities of GIS.
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Processing, IDP 2016, held in Barcelona, Spain, in October 2016.
The 11 revised full papers were carefully reviewed and selected from 52 submissions. The papers of this volume are organized in topical sections on machine learning theory with applications; intelligent data processing in life and social sciences; morphological and technological approaches to image analysis.
The GeoKnow project aims to make geospatial data accessible on the Web of Data, transforming the Web into a place where geospatial data can be published, queried, reasoned, and interlinked, according to Linked Data principles.
The article is devoted to the research, collection and analysis of geospatial data obtained by scrapping information from interactive maps or other public web resources. The data obtained can be used for the further research and identification of patterns or inaccuracies, as well as forecasting and visual presentation of the results. To solve the problem, an original concept is proposed for retrieving data that is on public servers, and which can be accessed using API (application program interface). This approach will be useful for research institutes, organizations for the formation of statistical and analytical reports and the provision of a spatial data set.
Spatial Data: the Needs of the Economy in the Context of Digitalization / E. Belogurova, V. Vorobyev, O. Gvozdev et al.; The Federal Service for State Registration, Cadastre and Cartography; National Research University Higher School of Economics; Institute for Scientiﬁ c Research of Aerospace Monitoring ”AEROCOSMOS“. – Moscow: HSE, 2020.
Proceedings of the 13th International Conference onWeb Search and Data Mining
Geospatial array DBMSs handle big georeferenced arrays. Due to the geospatial data peculiarities, many queries have tunable parameters with values not known in advance: users gradually tune them until they get a satisfactory result. This generates a series of queries with slightly different structures and very similar outputs. Modern array DBMSs spend the same efforts to answer each such query. BitFun provides novel bitmap indexing strategies to continuously re-index arrays during queries with similar mathematical functions. BitFun can be up to 8x faster than computing the results from scratch. We describe BitFun and offer lessons on real-world geospatial data, related to real practical tasks. A lesson involves tuning a math function parameter while the rich web GUI details the indexing process and query execution. Conference attendees will appreciate BitFun approaches, its performance, and learn its internals via fascinating lessons.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.