Inferring and Exploiting Categories for Next Location Prediction

Predicting the next location of a user based on their previous visiting pattern is one of the primary tasks over data from location based social networks (LBSNs) such as Foursquare. Many different aspects of these so-called “check-in” profiles of a user have been made use of in this task, including spatial and temporal information of check-ins as well as the social network information of the user. Building more sophisticated prediction models by enriching these check-in data by combining them with information from other sources is challenging due to the limited data that these LBSNs expose due to privacy concerns. In this paper, we propose a framework to use the location data from LBSNs, combine it with the data from maps for associating a set of venue categories with these locations. For example, if the user is found to be checking in at a mall that has cafes, cinemas and restaurants according to the map, all these information is associated. This category information is then leveraged to predict the next checkin location by the user. Our experiments with publicly available check-in dataset show that this approach improves on the state-of-the-art methods for location prediction.

An Investigation into the Link between UK Credit Union Characterisitics, Location and their Success

The unique characteristics of credit unions reduces the information asymmetry that is prevalent in credit making decisions, enabling them to provide loans where other financial institutions cannot. This makes them a potential tool in the fight against financial exclusion. Yet, the UK credit union movement is not regarded as being successful, even though there is evidence of much financial exclusion. This study is cross sectional in form, and evaluates characteristics that may contribute to the success of the UK credit union movement at national and regional level, in 2000. The findings are used to consider the impact of recent regulatory changes on the movement. The key findings are that there is a significant relationship between the success of a credit union, its size and the deprivation of the ward from which it sources its members. More specifically, larger credit unions and those located in more affluent wards, are more successful. Affiliation to the Irish League of Credit Unions and having a common bond of occupation, are also found to be contributing factors to credit union success. These results are taken as providing support for the recent changes implemented by the Financial Services Authority (FSA), which is likely to result in the emergence of larger credit unions (through mergers), run by appropriately qualified persons, serving a more mixed-income membership base. It is, however, noted that the history of the UK movement is one of missed opportunities and only time will tell whether credit unions have the wherewithal to accept current opportunities.