4 research outputs found

    Geographical places as a personalisation element: extracting profiles from human activities and services of visited places in mobility logs

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    Collecting personal mobility traces of individuals is currently applicable on a large scale due to the popularity of position-aware mobile phones. Statistical analysis of GPS data streams, collected with a mobile phone, can reveal several interesting measures such as the most frequently visited geographical places by some individual. Applying probabilistic models to such data sets can predict the next place to visit, and when. Several practical applications can utilise the results of such analysis. Current state of the art, however, is limited in terms of the qualitative analysis of personal mobility logs. Without explicit user-interactions, not much semantics can be inferred from a GPS log. This work proposes the utilisation of the common human activities and services provided at certain place types to extract semantically rich profiles from personal mobility logs. The resulting profiles include spatial, temporal and generic thematic description of a user. The work introduces several pre-processing methods for GPS data streams, collected with personal mobile devices, which improved the quality of the place extraction process from GPS logs. The thesis also introduces a method for extracting place semantics from multiple data sources. A textual corpus of functional descriptions of human activities and services associated with certain geographic place types is analysed to identify the frequent linguistic patterns used to describe such terms. The patterns found are then matched against multiple textual data sources of place semantics, to extract such terms, for a collection of place types. The results were evaluated in comparison to an equivalent expert ontology, as well as to semantics collected from the general public. Finally, the work proposes a model for the resulting profiles, the necessary algorithms to build and utilise such profiles, along with an encoding mark-up language. A simulated mobile application was developed to show the usability and for evaluation of the resulting profiles

    An ontology of place and service types to facilitate place-affordance geographic information retrieval

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    In order to facilitate place-affordance queries on the Web, this work proposes the employment of an ontology of place and service types. While other works defined place-affordance by associating a place with its physical objects, the conceptual view of a place-affordance in this work is based on associating a place type with its typical service types, which is reflected in the ontology construction methodology. Preliminary results, as well as an overview of the current work, are briefly introduced

    What can I do there? Towards the automatic discovery of place-related services and activities

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    The current web is rich in geographically referenced data. Mining, retrieving and sharing these data raises the need for rich geographical place name resources that record spatial and thematic elements of geographical places. Here, possible services offered at a place and human activities that can be practised there are considered useful concepts to discover and encode in place name resources. Recognising this dimension of place description can enhance information retrieval tasks by extending the range of possible queries and search criteria that relate to different place instances. This work proposes an automatic approach for the identification and extraction of service and activity-related concepts from multiple resources of textual descriptions of geographical place types. Frequent affordance patterns are identified and then applied to a corpus of resources to extract service and activity types associated with specific geographical place types. The evaluation experiments undertaken demonstrate the potential value of the approach
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