Empowering a GIS with inductive learning capabilities: the case of INGENS

نویسندگان

  • Donato Malerba
  • Floriana Esposito
  • Antonietta Lanza
  • Francesca A. Lisi
  • Annalisa Appice
چکیده

Information given in topographic map captions or in GIS models is often insufficient to recognize interesting geographical patterns. Some prototypes of GIS have already been extended with a knowledge-base and some reasoning capabilities to support sophisticated map interpretation processes. Nevertheless, the acquisition of the necessary knowledge is still a demanding task for which machine learning techniques can be of great help. This paper presents INGENS, a prototypical GIS which integrates machine learning tools to assist users in the task of topographic map interpretation. The system can be trained to learn operational definitions of geographical objects that are not explicitly modeled in the database. INGENS has been applied to the task of Apulian map interpretation in order to discover geographic knowledge of interest to town planners. # 2002 Elsevier Science Ltd. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Data Mining Query Language for Knowledge Discovery in a Geographical Information System

Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly stored in a spatial database. An important application of spatial data mining methods is the extraction of knowledge from a Geographic Information System (GIS). INGENS (INductive GEographic iNformation System) is a pr...

متن کامل

SDMOQL: An OQL-based Data Mining Query Language for Map Interpretation Tasks

Spatial data mining denotes the extraction of patterns from both spatial and aspatial data, possibly stored in a spatial database. An important application of spatial data mining methods is the extraction of knowledge from a Geographic Information System. INGENS (Inductive Geographic Information System) is a prototype GIS which integrates data mining tools to assist users in their task of topog...

متن کامل

Presenting a paradigmatic model of empowering the learning culture of school teachers in Kermanshah

The purpose of this study was to present a paradigmatic model of empowering the learning culture of school teachers in Kermanshah. In this research, a qualitative research method based on grounded theory was used. The data were gathered using semi-structured interviews and deep ones of Teacher Training University Faculty Members of Kermanshah in Educational Science, Educational Management as we...

متن کامل

Land Use Classification of Remote Sensing Image with Gis Databased on Spatial Data Mining Techniques

Data mining techniques are studied to discover knowledge from GIS database and remote sensing image data in order to improve land use classification. Two learning granularities are proposed for inductive learning from spatial data, one is spatial object granularity, the other is pixel granularity. The characteristics and application scope of the two granularities are discussed. We also present ...

متن کامل

Presenting a paradigmatic model of empowering the learning culture of school teachers in Kermanshah

The purpose of this study was to present a paradigmatic model of empowering the learning culture of school teachers in Kermanshah. In this research, a qualitative research method based on grounded theory was used. The data were gathered using semi-structured interviews and deep ones of Teacher Training University Faculty Members of Kermanshah in Educational Science, Educational Management as we...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Computers, Environment and Urban Systems

دوره 27  شماره 

صفحات  -

تاریخ انتشار 2003