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Nowadays a great deal of attention is devoted to the issue of supporting big data analytics over big mobile social data. These data are generated by modern emerging social systems like Twitter, Facebook, Instagram, and so forth. Mining big mobile social data has been of great interest, as analyzing such data is critical for a wide spectrum of big data applications (e.g., smart cities). Among several...
In this paper, we introduce an original approach thatexploits timestamped geo-tagged messages posted by Twitter usersthrough their smartphones when they travel to trace their trips.An original clustering technique is presented, that groups similartrips to define tours and analyze the popular tours in relationwith local geo-located territorial resources. This objective is veryrelevant for emerging...
Nowadays Spatial Data Infrastructures are the best practice to publish huge amount of spatial data on the Web in an interoperable and distributed way. Nevertheless, this operation requires a significant effort, expertise and motivation to data providers. In this paper, we propose an original approach to support geo-data providers by automating the workflows for publishing geo-data and relative web...
The paper addresses the problem of e-memes (electronic memes) representation and identification in the blogosphere, and it aims at defining the basis of a new conceptual model. First, an ememe is formally defined as a conceptual information granule by means of an OWL schema; then a process is proposed to retrieve from the blogosphere the posts dealing with the ememe. The proposed process extracts...
In this paper we address the problem of e-memes (electronic memes) representation and identification in the blogosphere by a new conceptual model. We first formally define an ememe by means of an OWL schema, then a process is proposed to retrieve from the blogospheres the posts dealing with the ememe. Some measures are proposed to characterize the identified ememe instances such as their replication...
In this paper an original soft hierarchical Fuzzy Clustering algorithm is proposed, named Hierarchical Hyper-spherical Divisive Fuzzy C-Means (H2D-FCM), with the following characteristics: it generates a “soft” hierarchy in which a document can belong to several child clusters of a node, and the clusters in the same hierarchical level are more specific (general) than the clusters in the upper (lower)...
This paper describes Matrioshka GeoScent, a prototypal system able to answer uncertain location based queries submitted by a moving user. The user searches for georeferenced resources on the web, by entering topics keywords, and specify the uncertain spatio temporal condition on their location by specifying a time span. This last condition is a spatio-temporal constraint on the resources distance...
In this paper we propose a query disambiguation mechanism focalizing the query context by applying clustering to the results of a Web-search. The clusters are ranked to reflect a balance of their contents’ novelty and overall similarity with respect to the original query, and, from each of them, a disambiguated query is generated so as to potentially retrieve new documents focalized on the cluster...
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