Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
OICPM: An Interactive System to Find Interesting Co-location Patterns Using Ontologies
verfasst von : Xuguang Bao, Lizhen Wang, Qing Xiao
Erschienen in: Web and Big Data
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
In spatial data mining, the usefulness of co-location patterns is strongly limited by the huge amount of delivered co-location patterns. Although many methods have been proposed to reduce the number of co-location patterns, most of them do not guarantee that the extracted co-location patterns are interesting for the user for being generally based on statistical information. This demonstration presents OICPM, an interactive system to discover interesting co-location patterns based on ontologies. With OICPM, the user can find his/her real interesting ones from a massive amount of co-location patterns efficiently within only a few rounds of selection, and the mined interesting co-location patterns are filtered in order for better decision.