Now showing 1 - 10 of 13
  • Publication
    Robustness analyses for repeated mobility surveys in outdoor advertising
    A growing number of companies use mobility data in their day-to-day business. However, as the data grows older, new data has to be collected in order to keep applications up-to-date. Consequently, it is of great importance to know the impact that a different mobility sample may cause. This aspect of analysis has been largely neglected in mobility data mining research so far. In this paper we therefore analyze the robustness of performance measures with respect to a changed GPS sample in outdoor advertisement. The evaluation of outdoor advertising campaigns is a challenging application because it requires the evaluation of mobility data on a very fine spatial level. Thus, the application has a higher dependency on routes of individual test persons than classical mobility surveys. In our rob ustness analysis we apply bootstrapping and subsampling in order to measure the effect of a) a repeated mobility survey and b) a mobility survey of smaller size. We conduct our experiments on a real-world data set from Swiss outdoor advertising. Our results show that the effect is comparably small for a typical campaign and may be mitigated further by increasing the campaign size.
  • Publication
    Modeling micro-movement variability in mobility studies
    During the past years the interest in the exploitation of mobility information has increased significantly. Along with these interests, new demands on mobility data sets have been posed. One particular demand is the evaluation of movement data on a high level of spatial detail. The high dimensionality of geographic space, however, makes this requirement hard to fulfill. Even large mobility studies cannot guarantee to comprise all movement variation on a high level of detail. In this paper we present an approach to increase the variability of movement data on microscopic scale in order to achieve a better representation of population movement. Our approach consists of two steps. First, we perform a spatial aggregation of trajectory data in order to counteract sparseness and to preserve movement on macroscopic scale. Second, we disaggregate the data in geographic space based on traffic distribution knowledge using repeated simulation. Our approach is applied in a real-world business application for the Ger-man outdoor advertising industry to measure the performance of poster sites.
  • Publication
    Challenges and advantages of using GPS data in outdoor advertisement
    A growing number of companies use mobility data in their day-to-day business. Especially in the area of outdoor advertising, GPS devices have been successfully applied in order to measure poster performance in recent years. Based on personal mobility traces, the quality and precision of performance measures has increased significantly. However, the usage of GPS technology poses several challenges when applied to critical business processes. We will present several challenges and solutions which we developed in the last years of our mobility research with GPS data.
  • Publication
    Visit potential: A common vocabulary for the analysis of entity-location interactions in mobility applications
    A growing number of companies and public institutions use mobility data in their day-to-day business. One type of usage is the analysis of spatio-temporal interactions between mobile entities and geographic locations. In practice the employed measures depend on application demands and use context-specific terminology. Thus, a patchwork of measures has evolved which is not suitable for methodological research and interdisciplinary ex-change of ideas. The measures lack a systematic formalization and a uni-form terminology. In this paper we therefore systematically define meas-ures for entity-location interactions which we name visit potential. We provide a common vocabulary that can be applied for an entire class of mobility applications. We present two real-world scenarios which apply entity-location interaction measures and demonstrate how the employed measures can be precisely defined in terms of visit potential.
  • Publication
    Räumlich differenzierte Reichweiten für die Außenwerbung
    Der Raum ist seit jeher ein wichtiger Bestandteil der Außenwerbung. Aus plausiblen Gründen werden Plakatstandorte so gewählt, dass sie häufig von Menschen gesehen werden. Während jedoch der Raum bei der Wahl von Plakatstandorten schon immer ein entscheidendes Kriterium gewesen ist, spielt er bei der Leistungsbewertung und damit bei der Preisbildung von Plakatstandorten erst seit den vergangenen Jahren eine wichtige Rolle. Neue, GPS-basierte Messmethoden erlauben die räumlich differenzierte Ausweisung von Leistungswerten für beliebig zusammengestellte Kampagnen und Zielgruppen. In diesem Artikel stellen wir am Beispiel der Schweiz die alte und neue Methodik zur Erfassung von Reichweitenleistungen gegenüber. Anhand von Beispielen mit real existierenden Messdaten der schweizer Außenwerbung zeigen wir, wie die Außenwerbung durch räumlich differenzierende Verfahren in der Leistungsbewertung von Kampagnen profitiert.
  • Publication
    Spatial data mining in practice
    Almost any data can be referenced in geographic space. Such data permit advanced analyses that utilize the position and relationships of objects in space as well as geographic background information. Even though spatial data mining is still a young research discipline, in the past years research advances have shown that the particular challenges of spatial data can be mastered and that the technology is ready for practical application when spatial aspects are treated as an integrated part of data mining and model building. In this chapter in particular, we give a detailed description of several customer projects that we have carried out and which all involve customized data mining solutions for business relevant tasks. The applications range from customer segmentation to the prediction of traffic frequencies and the analysis of GPS trajectories. They have been selected to demonstrate key challenges, to provide advanced solutions and to arouse further research questions.
  • Publication
    Sample bias due to missing data in mobility surveys
    A growing number of companies use mobility information in their day-to-day business. One requirement thereby is that inference about population-wide mobility patterns can be made. Therefore, it is not only important to find mobility patterns in a given data sample but also to assert their validity for the total population. This aspect of analysis has been largely neglected in mobility data mining research, which limits the applicability of the whole algorithmic field. In this paper we will analyze one aspect of sample bias due to incomplete mobility data. We will provide a systematic approach to detect dependencies between mobility behavior, socio-demography and missing data. Further, we apply the approach to a large GPS mobility survey in Switzerland and show that our concerns are justified and require attention in future research. We hope that our paper will raise the awareness that representativity of mobile behavior cannot be taken for granted in mobility surveys du e to missing data and is a research direction of utmost importance.
  • Publication
    A general pedestrian movement model for the evaluation of mixed indoor-outdoor poster campaigns
    Over the last few years new measurement technology has revolutionized the performance measurement in outdoor advertising. A handful of pioneer countries trace personal mobility now via GPS devices, which allows for precise performance results of arbitrarily positioned outdoor poster campaigns. However, GPS technology has the drawback that it cannot be applied indoors due to signal loss. In Switzerland and Germany many valuable posters are situated in public buildings such as train stations or shopping malls and their evaluation is of high interest. In this paper we therefore present a new approach for the evaluation of mixed indoor-outdoor campaigns. Our approach consists of a general pedestrian movement model in restricted spaces which can be integrated into standard trajectory evaluation. Our approach has been implemented for 27 major train stations in Switzerland.
  • Publication
    Modelling missing values for audience measurement in outdoor advertising using GPS data
    ( 2009) ; ; ;
    Pasquier, M.
    ;
    Hofmann, Urs
    ;
    Mende, F.
    GPS technology has made it possible to evaluate the performance of outdoor advertising campaigns in an objective manner. Given the GPS trajectories of a sample of test persons over several days, their passages with arbitrary poster campaigns can be calculated. However, inference is complicated by the early dropout of persons. Other than in most demonstrations of spatial data mining algorithms where the structure of the data sample is usually disregarded, poster performance measures such as reach and gross impressions evolve continuously over time and require non-intermittent observations. In this paper, we investigate the applicability of survival analysis to compensate for missing measurement days. We formalize the task of modeling the visit potential of geographic locations based on trajectory data as our variable of interest results from dispersed events in space-time. We perform experiments on the cities of Zurich and Bern simulating different dropout mechanisms and dropout rates and show the adequacy of the applied method. Our modeling technique is at present part of a business solution for the Swiss outdoor advertising branch and serves as pricing basis for the majority of Swiss poster locations.
  • Publication
    Handling missing values in GPS surveys using survival analysis
    ( 2009) ; ; ;
    Pasquier, M.
    ;
    Hofmann, Urs
    ;
    Mende, F.
    GPS technology has made it possible to evaluate the performance of outdoor advertising campaigns in an objective manner. Given the GPS trajectories of a sample of test persons over several days, their passages with arbitrary poster campaigns can be calculated. However, inference is complicated by the early dropout of persons. Other than in most demonstrations of spatial data mining algorithms where the structure of the data sample is usually disregarded, poster performance measures such as reach and gross impressions evolve continuously over time and require non-intermittent observations. In this paper, we investigate the applicability of survival analysis to compensate for missing measurement days. We formalize the task of modeling the visit potential of geographic locations based on trajectory data as our variable of interest results from dispersed events in space-time. We perform experiments on the cities of Zurich and Bern simulating different dropout mechanisms and dropout rates and show the adequacy of the applied method. Our modeling technique is at present part of a business solution for the Swiss outdoor advertising branch and serves as pricing basis for the majority of Swiss poster locations.