A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called space-in-time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios

A spatial multi-criteria model for the evaluation of land redistribution plans

A planning support system for land consolidation has been developed that has, at its heart, an expert system called LandSpaCES (Land Spatial Consolidation Expert System) which contains a "design module" that generates alternative land redistributions under different scenarios and an "evaluation module" which integrates GIS with multi-criteria decision making for assessing these alternatives. This paper introduces the structural framework of the latter module which has been applied using a case study in Cyprus. Two new indices are introduced: the "parcel concentration coefficient" for measuring the dispersion of parcels; and the "landowner satisfaction rate" for predicting the acceptance of the land redistribution plan by the landowners in terms of the location of their new parcels. These two indices are used as criteria for the evaluation of the land redistribution alternatives and are transferable to any land consolidation project. Moreover, a modified version of the ratio estimation procedure, referred to as the "qualitative rating method" for assigning weights to the evaluation criteria, is presented, along with a set of non-linear value functions for standardizing the performance scores of the alternatives and incorporating expert knowledge for five evaluation criteria. The application of the module showed that it is a powerful new tool for the evaluation of alternative land redistribution plans that could be implemented in other countries after appropriate adjustments. A broader contribution has also been made to spatial planning processes, which might follow the methodology and innovations presented in this paper

A visual analytics framework for spatio-temporal analysis and modelling

To support analysis and modelling of large amounts of spatio-temporal data having the form of spatially referenced time series (TS) of numeric values, we combine interactive visual techniques with computational methods from machine learning and statistics. Clustering methods and interactive techniques are used to group TS by similarity. Statistical methods for TS modelling are then applied to representative TS derived from the groups of similar TS. The framework includes interactive visual interfaces to a library of modelling methods supporting the selection of a suitable method, adjustment of model parameters, and evaluation of the models obtained. The models can be externally stored, communicated, and used for prediction and in further computational analyses. From the visual analytics perspective, the framework suggests a way to externalize spatio-temporal patterns emerging in the mind of the analyst as a result of interactive visual analysis: the patterns are represented in the form of computer-processable and reusable models. From the statistical analysis perspective, the framework demonstrates how TS analysis and modelling can be supported by interactive visual interfaces, particularly, in a case of numerous TS that are hard to analyse individually. From the application perspective, the framework suggests a way to analyse large numbers of spatial TS with the use of well-established statistical methods for TS analysis

Visual analysis design to support research into movement and use of space in Tallinn: A case study

We designed and applied interactive visualisation to help an urban study group investigate how suburban residents in the Tallinn Metropolitan Area (Estonia) use space in the city. We used mobile phone positioning data collected from suburban residents together with their socio-economic characteristics. Land-use data provided geo-context that helped characterise visited locations by suburban residents. Our interactive visualisation design was informed by a set of research questions framed as identification, localisation and comparison tasks. The resulting prototype offers five linked and coordinated views of spatial, temporal, socio-economic characteristics and land-use aspects of data. Brushing, sorting and filtering provide visual means to identify similarities between individuals and facilitate the identification, localisation and comparison of patterns of use of urban space. The urban study group was able to use the prototype to explore their data and address their research questions in a more flexible way than previously possible. Initial feedback was positive. The prototype was found to support the research and facilitate the discovery of patterns and relations among groups of participants and their movements

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Tagging amongst friends: an exploration of social media exchange on mobile devices

Mobile social software tools have great potential in transforming the way users communicate on the move, by augmenting their everyday environment with pertinent information from their online social networks. A fundamental aspect to the success of these tools is in developing an understanding of their emergent real-world use and also the aspirations of users; this thesis focuses on investigating one facet of this: the exchange of social media. To facilitate this investigation, three mobile social tools have been developed for use on locationaware smartphone handsets. The first is an exploratory social game, 'Gophers' that utilises task oriented gameplay, social agents and GSM cell positioning to create an engaging ecosystem in which users create and exchange geotagged social media. Supplementing this is a pair of social awareness and tagging services that integrate with a user's existing online social network; the 'ItchyFeet' service uses GPS positioning to allow the user and their social network peers to collaboratively build a landscape of socially important geotagged locations, which are used as indicators of a user's context on their Facebook profile; likewise 'MobiClouds' revisits this concept by exploring the novel concept of Bluetooth 'people tagging' to facilitate the creation of tags that are more indicative of users' social surroundings. The thesis reports on findings from formal trials of these technologies, using groups of volunteer social network users based around the city of Lincoln, UK, where the incorporation of daily diaries, interviews and automated logging precisely monitored application use. Through analysis of trial data, a guide for designers of future mobile social tools has been devised and the factors that typically influence users when creating tags are identified. The thesis makes a number of further contributions to the area. Firstly, it identifies the natural desire of users to update their status whilst mobile; a practice recently popularised by commercial 'check in' services. It also explores the overarching narratives that developed over time, which formed an integral part of the tagging process and augmented social media with a higher level meaning. Finally, it reveals how social media is affected by the tag positioning method selected and also by personal circumstances, such as the proximity of social peers