Spatio-semantic user profiles in location-based social networks

Knowledge of users’ visits to places is one of the keys to understanding their interest in places. User-contributed annotations of place, the types of places they visit, and the activities they carry out, add a layer of important semantics that, if considered, can result in more refined representations of user profiles. In this paper, semantic information is summarised as tags for places and a folksonomy data model is used to represent spatial and semantic relationships between users, places, and tags. The model allows simple co-occurrence methods and similarity measures to be applied to build different views of personalised user profiles. Basic profiles capture direct user interactions, while enriched profiles offer an extended view of users’ association with places and tags that take into account relationships in the folksonomy. The main contributions of this work are the proposal of a uniform approach to the creation of user profiles on the Social Web that integrates both the spatial and semantic components of user-provided information, and the demonstration of the effectiveness of this approach with realistic datasets

Towards location privacy awareness on geo-social networks

With the current trend of embedding location services within social networks, an ever growing amount of users' spatiotemporal tracks are being collected and used to generate user profiles. Issues of personal privacy and especially those stemming from tracking user location become more important to address. In this work, it is argued that support of location privacy awareness within social networks is needed to maintain the users' trust in their services. Current practices of pre-configuring location disclosure settings have been shown to be limited, where users' sense of location privacy dynamically change with context. In this paper, location privacy awareness is considered within a composite view of place, time and social data recorded in user profiles. The paper examines the possible threats to personal privacy from exposure of this data and the design of feedback tools to allow users to control their privacy. A user study is used to examine the impact of the feedback provided on users' perception of privacy and the link between their privacy concerns and their attitude towards using the geo-social network. Findings confirm the strong need for more transparent access to and control over user location profiles, and guide the proposal of recommendations to the design of more privacy-sensitive geo-social networks

Order in space: a general formalism for spatial reasoning

In this paper we propose a general approach for reasoning in space. The approach is composed of a set of two general constraints to govern the spatial relationships between objects in space, and two rules to propagate relationships between those objects. The approach is based on a novel representation of the topology of the space as a connected set of components using a structure called adjacency matrix which can capture the topology of objects of different complexity in any space dimension. The formalism is used to explain spatial compositions resulting in indefinite and definite relations and it is shown to be applicable to reasoning in the temporal domain. The main contribution of the formalism is that it provides means for constructing composition tables for objects with arbitrary complexity in any space dimension. A new composition table between spatial objects of different types is presented. A major advantage of the method is that reasoning between objects of any complexity can be achieved in a defined limited number of steps. Hence, the incorporation of spatial reasoning mechanisms in spatial information systems becomes possible

Towards a general theory for modelling qualitative space

Qualitative spatial representation and reasoning are techniques for modeling and manipulating objects and relationships in space. Finding ways for defining the complete and sound (physically plausible) set of relationships between spatial objects is a prerequisite for the development and realization of qualitative representation and reasoning formalisms. Establishing the set of sound relationships is a complicated task especially when complex objects are considered. Hence, current approaches to qualitative representation and reasoning are limited to handling simple spatial objects. In this paper, we introduce a constraint-based approach to qualitative representation of topological relationships by defining a set of general soundness rules. The rules reduce the combinatorial set of relations produced by the method to the complete and physically possible ones. The rules are general and apply to objects of arbitrary complexity and together with the representation and reasoning formalism form a theory for qualitative space

Enriching user profiles using geo-social place semantics in geo-folksonomies

Geo-folksonomies link social web users to geographic places through the tags users choose to label the places with. These tags can be a valuable source of information about the user’s perception of place and can reflect their experiences and activities in the places they label. By analysing the associations between users, places and tags, an understanding of a place and its relationships with other places can be drawn. This place characterisation is unique, dynamic and reflects the perception of a particular user community that generated the geo-folksonomy. In this work, an approach is proposed to analysing geo-folksonomies that builds on and extends existing statistical methods by considering specific concepts of relevance to geographic place resources, namely, place types and place-related activities, and by building a place ontology to encode those concepts and relationships. The folksonomy analysis and evaluation are demonstrated using a realistic geo-folksonomy data set. The resulting ontology is used to build user profiles from the folksonomy. The derived profiles reflect the association between users and the specific places they tag as well as other places with relevant associated place type and activities. The methods proposed here provide the potential for many interesting and useful applications, including the harvesting of useful insight on geographic space and employing the derived user profiles to enhance the search experience and to identify similarities between users based on their association to geographic places

Mining topological relations from the web

Topological relations between geographic regions are of interest in many applications. When the exact boundaries of regions are not available, such relations can be established by analysing natural language information from web documents. In particular we demonstrate how redundancy-based techniques can be used to acquire containment and adjacency relations, and how fuzzy spatial reasoning can be employed to maintain the consistency of the resulting knowledge base