Motive-based Search - Computing Regions from Large Knowledge Bases using Geospatial Coordinates

Liliya Avdiyenko, Martin Nettling, Christiane Lemke, Matthias Wauer, Axel-Cyrille Ngonga Ngomo, Andreas Both

Abstract

To create a better search experience for end users and to satisfy their actual intents even for vaguely formulated queries, a contemporary search engine has to go beyond simple keyword-based retrieval concepts. For a geospatial search, where user queries can be quite complex such as "places for winter sport holidays and culture in Central Europe", we introduce the notion of geospatial motifs denoting traits of geographical regions. Defining a motif by a set of geospatial entities with certain characteristics, we present an approach to inferring important regions for the motif based on density of these entities. The evaluation of the approach for several motifs showed that the inferred regions are among the most popular places for a motif of interest according to the opinion of several experts and official rankings. Thus, we claim that the presented semi-automatic process of detecting regions for geospatial motifs can contribute to more powerful and flexible search applications which are able to answer user queries containing complex geospatial concepts.

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Paper Citation


in Harvard Style

Avdiyenko L., Nettling M., Lemke C., Wauer M., Ngonga Ngomo A. and Both A. (2015). Motive-based Search - Computing Regions from Large Knowledge Bases using Geospatial Coordinates . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 469-474. DOI: 10.5220/0005635004690474


in Bibtex Style

@conference{kdir15,
author={Liliya Avdiyenko and Martin Nettling and Christiane Lemke and Matthias Wauer and Axel-Cyrille Ngonga Ngomo and Andreas Both},
title={Motive-based Search - Computing Regions from Large Knowledge Bases using Geospatial Coordinates},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={469-474},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005635004690474},
isbn={978-989-758-158-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Motive-based Search - Computing Regions from Large Knowledge Bases using Geospatial Coordinates
SN - 978-989-758-158-8
AU - Avdiyenko L.
AU - Nettling M.
AU - Lemke C.
AU - Wauer M.
AU - Ngonga Ngomo A.
AU - Both A.
PY - 2015
SP - 469
EP - 474
DO - 10.5220/0005635004690474