Location-Based services - A crescente importância da localização

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Multi-agent system for personalization of location-based services

The current ubiquitous network access and increase in network bandwidth are driving the sales of mobile location-aware user devices and, consequently, the development of context-aware applications, namely location-based services. The goal of this project is to provide consumers of location-based services with a richer end-user experience by means of service composition, personalization, device adaptation and continuity of service. Our approach relies on a multi-agent system composed of proxy agents that act as mediators and providers of personalization meta-services, device adaptation and continuity of service for consumers of pre-existing location-based services. These proxy agents, which have Web services interfaces to ensure a high level of interoperability, perform service composition and take in consideration the preferences of the users, the limitations of the user devices, making the usage of different types of devices seamless for the end-user. To validate and evaluate the performance of this approach, use cases were defined, tests were conducted and results gathered which demonstrated that the initial goals were successfully fulfilled.

Scenario Analysis of the Location Based Services Industry

Tutkimuksen tavoitteena oli luoda erilaisia skenaariota paikka riippuvaisten palveluiden toimialan tulevaisuudesta. Tunnistamalla nykyisiä sekä tulevia alaa edistäviä ja rajoittavia tekijöitä kolme skenaariota luotiin, jotka mahdollisesti kuvaisivat paikka riippuvaisten palveluiden toimialaa viiden vuoden päästä: "Massa spämmaus", "Raju operaattori kilpailu - nousevia yksityisyyden huolia" sekä "Nokian ajama kolmannen sukupolven verkot tulevat ennen odotettua" Skenaarioiden luomiseksi ensimmäinen osa tutkimuksesta keskittyi erilaisiin skenaarioiden kirjoitus prosesseihin ja niissä huomioitaviin asioihin. Tutkimuksen tarkoituksiin sopiva skenaarion kirjoitusprosessi esiteltiin, minkä jälkeen| paikkariippuvaisten palveluiden toimialaa käsiteltiin. Lopuksi itse skenaariot esiteltiin ja nimettiin skenaarioiden teemojen mukaan. Tutkimuksen johtopäätös on, ettei toimialan tulevaisuutta voida ennustaa riittävällä varmuudella. Tutkimuksen arvo kuitenkin piilee sen antamassa ymmärryksessä liittyen tekijöihin, jotka tulevat päättämään alan tulevaisuuden sekä skenaariossa, joita nämä tekijät voivat muodostaa.

Optimizing Mobile Java Location-Based Services in Symbian OS

This thesis evaluates methods for obtaining high performance in applications running on the mobile Java platform. Based on the evaluated methods, an optimization was done to a Java extension API running on top the Symbian operating system. The API provides location-based services for mobile Java applications. As a part of this thesis, the JNI implementation in Symbian OS was also benchmarked. A benchmarking tool was implemented in the analysis phase in order to implement extensive performance test set. Based on the benchmark results, it was noted that the landmarks implementation of the API was performing very slowly with large amounts of data. The existing implementation proved to be very inconvenient for optimization because the early implementers did not take performance and design issues into consideration. A completely new architecture was implemented for the API in order to provide scalable landmark initialization and data extraction by using lazy initialization methods. Additionally, runtime memory consumption was also an important part of the optimization. The improvement proved to be very efficient based on the measurements after the optimization. Most of the common API use cases performed extremely well compared to the old implementation. Performance optimization is an important quality attribute of any piece of software especially in embedded mobile devices. Typically, projects get into trouble with performance because there are no clear performance targets and knowledge how to achieve them. Well-known guidelines and performance models help to achieve good overall performance in Java applications and programming interfaces.

Wireless privacy and personalized location-based services: the challenge of translating the legal framework into business practices

L'avancement des communications sans-fil permet l'obtention de nouveaux services bases sur l'habileté des fournisseurs de services sans-fil à déterminer avec précision, et avec l'utilisation de technologies de pistage, la localisation et position géographiquement d'appareils sans-fil Cette habileté permet d'offrir aux utilisateurs de sans-fil de nouveaux services bases sur la localisation et la position géographique de leur appareil. Le développement des services basés sur la localisation des utilisateurs de sans-fil soulevé certains problèmes relatifs à la protection de la vie privée qui doivent être considérés. En effet, l'appareil sans-fil qui suit et enregistre les mouvements de I 'utilisateur permet un système qui enregistre et entrepose tous les mouvements et activités d'un tel utilisateur ou encore qui permet l'envoi de messages non anticipes à ce dernier. Pour ce motif et afin de protéger la vie privée des utilisateurs de sans-fil, une compagnie désirant développer ou déployer une technologie permettant d'offrir ce genre de services personnalisés devra analyser l'encadrement légal touchant la protection des données personnelles--lequel est dans certains cas vague et non approprié à ce nouveau contexte--ainsi que la position de l'industrie dans ce domaine, et ce, afin d'être en mesure de traduire cet encadrement en pratiques commerciales. Cette analyse permettra d'éclairer le fournisseur de ces services sur la façon d'établir son modèle d'affaires et sur le type de technologie à développer afin d'être en mesure de remédier aux nouveaux problèmes touchant la vie privée tout en offrant ces nouveaux services aux utilisateurs de sans-fil.

Mixed spatial and nonspatial problems in location based services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.

Location-based Marketing: the academic framework

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Innovation process management of complex consumer products and services in new innovation paradigm – case location based business

Innovation is the word of this decade. According to innovation definitions, without positive sales impact and meaningful market share the company’s product or service has not been an innovation. Research problem of this master thesis is to find out what is the innovation process of complex new consumer products and services in new innovation paradigm. The objective is to get answers to two research questions: 1) What are the critical success factors what company should do when it is implementing the paradigm change in mass markets consumer business with complex products and services? 2) What is the process or framework one firm could follow? The research problem is looked from one company’s innovation creation process, networking and organization change management challenges point of views. Special focus is to look the research problem from an existing company perspective which is entering new business area. Innovation process management framework of complex new consumer products and services in new innovation paradigm has been created with support of several existing innovation theories. The new process framework includes the critical innovation process elements companies should take into consideration in their daily activities when they are in their new business innovation implementing process. Case company location based business implementation activities are studied via the new innovation process framework. This case study showed how important it is to manage the process, look how the target market and the competition in it is developing during company’s own innovation process, make decisions at right time and from beginning plan and implement the organization change management as one activity in the innovation process. In the end this master thesis showed that all companies need to create their own innovation process master plan with milestones and activities. One plan does not fit all, but all companies can start their planning from the new innovation process what was introduced in this master thesis.

Searching the world wide web for local services and facilities: A review on the patterns of location-based queries

Many queries sent to search engines refer to specific locations in the world. Location-based queries try to find local services and facilities around the user’s environment or in a particular area. This paper reviews the specifications of geospatial queries and discusses the similarities and differences between location-based queries and other queries. We introduce nine patterns for location-based queries containing either a service name alone or a service name accompanied by a location name. Our survey indicates that at least 22% of the Web queries have a geospatial dimension and most of these can be considered as location-based queries. We propose that location-based queries should be treated different from general queries to produce more relevant results.