Discovering spatial interaction patterns of near repeat crime by spatial association rules mining
نویسندگان
چکیده
منابع مشابه
Discovering Spatial Interaction Patterns
Advances in sensing and satellite technologies and the growth of Internet have resulted in a vast amount of uncertain spatial data. Extracting interaction patterns from these uncertain data is a challenging task. In this paper, we propose to model the spatial features in a continuous space through the use of influence functions. For each feature type, we build an influence map that captures the...
متن کاملMining spatial association rules in census data
In this paper we propose a method for the discovery of spatial association rules, that is, association rules involving spatial relations among (spatial) objects. The method is based on a multi-relational data mining approach and takes advantage of the representation and reasoning techniques developed in the field of inductive logic programming (ILP). In particular, the expressive power of predi...
متن کاملMining Spatial Association Rules with Geostatistics
In 1962, G. Matheron introduced the term geostatistics to describe a scientific approach to evaluate problems in geology and mining, from ore reserve estimation to grade control. Geostatistics provides statistical methods used to describe spatial relationships among sample data and to apply this analysis to the prediction of spatial and temporal phenomena. They are used to explain spatial patte...
متن کاملMining Spatial Association Rules from Image Databases
In this paper, we propose a mining approach for efficiently finding implicit spatial relations of objects in images. An effective representation for spatial relations is first designed, from which primary spatial relations can be easily obtained. The proposed primary spatial relations have a good characteristic of symmetry, which can greatly reduce the number of candidate itemsets in the mining...
متن کاملUser Constraints in Discovering Association Rules Mining
This paper introduces a new algorithm called User Association Rules Mining (UARM) for solving the problem of generating inadequate large number of rules in mining association technique using a fuzzy logic method [1, 2]. In order to avoid user’s defined threshold mistakes, the user has flexibility to determine constraints based on a set of features. In comparison with other well-known and widely...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2020
ISSN: 2045-2322
DOI: 10.1038/s41598-020-74248-w