SpaceRank: Using PageRank to estimate location importance
Stefano De Sabbata, Stefano Mizzaro, Luca Vassena
Abstract
Stefano De Sabbata, Stefano Mizzaro, Luca Vassena
Abstract
Abstract. The recent advance of Web 2.0 and the rapid develop-ment of online social websites have created a large interest in the collection and analysis of social data. Although social data mining is usually done on the Web, social data do not exist in the virtual world only, but also in the physical one. Mining real people positions can allow to derive the importance, or popularity, of places in the real world. The collected data can be useful for many applications. In this paper we define SpaceRank, an approach to mining people positions, on the basis of the PageRank algorithm. Preliminary experimental re-sults show that SpaceRank computes a notion of location importance that seems reasonable and is different from more classical indexes. 1
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Abstract. The recent advance of Web 2.0 and the rapid develop-ment of online social websites have created a large interest in the collection and analysis of social data. Although social data mining is usually done on the Web, social data do not exist in the virtual world only, but also in the physical one. Mining real people positions can allow to derive the importance, or popularity, of places in the real world. The collected data can be useful for many applications. In this paper we define SpaceRank, an approach to mining people positions, on the basis of the PageRank algorithm. Preliminary experimental re-sults show that SpaceRank computes a notion of location importance that seems reasonable and is different from more classical indexes. 1
Key concepts: PageRank, Popularity, Computer science, Data science, Web mining, Real world data, Data mining, World Wide Web