Abstract
This paper introduces a new map browser of location based contents (LBC) that summarizes area characteristics. Recently various web map services have been widely used to search web contents. As LBC increase, browsing a number of LBC which are viewed as POI (point of interest) on a geographical map becomes inefficient. We tackle this issue by using AOI (area of interest) instead of POI. With the AOI a user can instantly find area characteristics without viewing each content of POI. We assume that semantically homogeneous and geographically distinguishable areas are suitable for the AOI. The AOI is formed by geo-semantic clustering which is a co-clustering that takes into account both geographical and semantic aspects of POI information. By the experiment using real LBC on the web, we confirmed our method has potential to extract good AOI.
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Masutani, O., Iwasaki, H. (2007). BEIRA: A Geo-semantic Clustering Method for Area Summary. In: Benatallah, B., Casati, F., Georgakopoulos, D., Bartolini, C., Sadiq, W., Godart, C. (eds) Web Information Systems Engineering – WISE 2007. WISE 2007. Lecture Notes in Computer Science, vol 4831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76993-4_10
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DOI: https://doi.org/10.1007/978-3-540-76993-4_10
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