Information technology and social media have been a driving force in the economy and have transformed all aspects of business in recent decades. Understanding social networks is necessary to evaluate their impacts and examine key business issues involving information and technological innovations. The dissertation contains three chapters exploring those issues. In the first chapter, I propose an optimal procurement mechanism for mobile data offloading, covering both technological and business aspects. The unprecedented growth of cellular traffic driven by web surfing, video streaming, and cloud-based services is creating challenges for cellular service providers to fulfill the unmet demand. My present work contributes to the existing literature by developing an analytical model, which considers the unique challenge of integrating the longer range cellular resource and shorter range WiFi hotspots. In the second chapter, I examine the effect of a social network on prediction markets using a controlled laboratory experiment. In prediction markets, people place bets on events that they think are most likely to happen, thus revealing in a sense the nature of their private information. Through a randomized experiment, I show that when the cost of information acquisition is low, a social-network-embedded prediction market outperforms a non-networked prediction market. The third chapter studies different forms of social learning in the context of location-based networks: observational learning and the saliency effect. In recent years, the location-sensing mobile devices offer geographic location capabilities to share users' information about their locations with their friends. In our context, observational learning corresponds to the fact that "check-ins" made by friends help users learn the quality information of a venue; the saliency effect refers to that check-ins lead some of the uninformed consumers to discover a new venue. / text

Chim, Ho Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 58-62). / Abstracts in English and Chinese. / Acknowledgements --- p.i / Abstract --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Objectives --- p.1 / Chapter 1.2 --- Motivations --- p.1 / Chapter 1.3 --- Problem Statement --- p.2 / Chapter 1.4 --- Camera Self-Localization Approaches --- p.3 / Chapter 1.4.1 --- Based on Calibration Patterns --- p.3 / Chapter 1.4.2 --- Based on Self-calibration --- p.3 / Chapter 1.4.3 --- Based on Shape and Motion --- p.4 / Chapter 1.4.4 --- The Proposed Approach - Based on Junctions --- p.5 / Chapter 1.5 --- Thesis Organization --- p.6 / Chapter 2 --- Previous Work --- p.7 / Chapter 2.1 --- Camera Self-Localization --- p.7 / Chapter 2.1.1 --- Parallel Plane Features --- p.7 / Chapter 2.1.2 --- Parallelepiped Features --- p.8 / Chapter 2.1.3 --- Single View Geometric Features --- p.8 / Chapter 2.1.4 --- Shape and Motion --- p.8 / Chapter 2.1.5 --- Other Estimation Methods --- p.9 / Chapter 2.2 --- Feature Correspondences Establishment --- p.9 / Chapter 2.2.1 --- Feature-based Object Recognition --- p.9 / Chapter 2.2.2 --- Model-based Object Recognition --- p.10 / Chapter 3 --- Preliminaries --- p.11 / Chapter 3.1 --- Perspective Camera Model --- p.11 / Chapter 3.2 --- Camera Pose from Point Correspondences --- p.15 / Chapter 3.3 --- Camera Pose from Direction Correspondences --- p.16 / Chapter 4 --- A Junction-based Approach --- p.18 / Chapter 4.1 --- Use of Junction Correspondences for Determining Camera Pose --- p.18 / Chapter 4.1.1 --- Constraints from Point Information --- p.19 / Chapter 4.1.2 --- Constraint from Direction Information --- p.21 / Chapter 4.1.3 --- Junction Triplet Correspondences --- p.22 / Chapter 4.2 --- Extraction of Junctions and Junction Triplets from Image --- p.24 / Chapter 4.2.1 --- Handling Image Data --- p.24 / Chapter 4.2.2 --- Bridging Lines --- p.25 / Chapter 4.2.3 --- """L""-junctions" --- p.26 / Chapter 4.2.4 --- """Y"" and ""Adjunctions" --- p.27 / Chapter 4.2.5 --- Junction Triplets --- p.28 / Chapter 4.3 --- Establishment of the First Junction Triplet Correspondence --- p.30 / Chapter 4.3.1 --- Ordered Junction Triplets from Model --- p.30 / Chapter 4.3.2 --- A Junction Hashing Scheme --- p.31 / Chapter 4.4 --- Establishment of Points Correspondence --- p.33 / Chapter 4.4.1 --- Viewing Sphere Tessellation --- p.33 / Chapter 4.4.2 --- Model Views Synthesizing --- p.35 / Chapter 4.4.3 --- Affine Coordinates Computation --- p.35 / Chapter 4.4.4 --- Hash Table Filling --- p.38 / Chapter 4.4.5 --- Hash Table Voting --- p.38 / Chapter 4.4.6 --- Hypothesis and Confirmation --- p.39 / Chapter 4.4.7 --- An Example of Geometric Hashing --- p.40 / Chapter 5 --- Experimental Results --- p.43 / Chapter 5.1 --- Results from Synthetic Image Data --- p.43 / Chapter 5.2 --- Results from Real Image Data --- p.45 / Chapter 5.2.1 --- Results on Laboratory Scenes --- p.46 / Chapter 5.2.2 --- Results on Outdoor Scenes --- p.48 / Chapter 6 --- Conclusion --- p.51 / Chapter 6.1 --- Contributions --- p.51 / Chapter 6.2 --- Advantages --- p.52 / Chapter 6.3 --- Summary and Future Work --- p.52 / Chapter A --- Least-Squares Method --- p.54 / Chapter B --- RQ Decomposition --- p.56 / Bibliography --- p.58

As a part of the Tourist Information Provider (TIP) system, this project focuses on creating a photo gallery service in the TIP system, which allows users to share, browse and categorize their photos. The core of this project is to provide users a location-based photo browsing. The system provides photos which are taken in the current user's location. We considered privacy control on photos that users uploaded. A photo owner is able to sign an access level to each of their photos and permit different users to access them. We also considered reusing resources. The system allows a user to use an URL of a photo in the system in stead of uploading the photo from the local computer. The system also provides a URL of each photo in order to use the photo on other web places, e.g., Blogs. We use tags and photo metadata Eixf to categorize photos.

In Mobile Ad Hoc NETworks (MANETs) autonomous nodes act both as traffic originators and forwarders to form a multi-hop network. Out-of-range nodes are reachable through a process called routing, which is a challenging task due to the constraints of bandwidth and battery power. Stateless location-based routing schemes have been proposed to avoid complex route discovery and maintenance, whereby nodes make routing decisions based solely on the knowledge of their location, the location of their neighbors, and the location of the destination. Natural routing schemes based on these prerequisites suffer from problems like local maxima or loops. We mitigate those problems by proposing randomized routing algorithms, which outperform others in terms of the packet delivery ratio and throughput. The prerequisite for location-based routing is knowing the location of a node. Location information is more widely useful anyway for location-aware applications like security, health care, robotics, navigation etc. Locating a node indoors remains a challenging problem due to the unavailability of GPS signals under the roof. For this goal we choose the RSS (Received Signal Strength) as the relevant attribute of the signal due to its minimal requirements on the RF technology of the requisite modules. Then profiling based localization is considered that does not rely on any channel model (range-based) or the connectivity information (range-free), but rather exploits the context of a node to infer that information into the estimation. We propose a RSS profiling based indoor localization system, dubbed LEMON, based on low-cost low-power wireless devices that offers better accuracy than other RSS-based schemes. We then propose a simple RSS scaling trick to further improve the accuracy of LEMON. Furthermore, we study the effect of the node orientation, the number and the arrangement of the infrastructure nodes and the profiled samples, leading us to further insights about what can be effective node placement and profiling. We also consider alternate formulations of the localization problem, as a Bayesian network model as well as formulated in a combinatorial fashion. Then performance of different localization methods is compared and again LEMON ensures better accuracy. An effective room localization algorithm is developed, and both single and multiple channels are used to test its performance. Furthermore, a set of two-step localization algorithms is designed to make the LEMON robust in the presence of noisy RSS and faulty device behavior.

Largely driven by advances in communication and information technology, such as the increasing availability and accuracy of GPS technology and the miniaturization of wireless communication devices, Location–Based Services (LBS) are continuously gaining popularity. Innovative LBSes integrate knowledge about the users into the service. Such knowledge can be derived by analyzing the location data of users. Such data contain two unique dimensions, space and time, which need to be analyzed. The objectives of this thesis are three–fold. First, to extend popular data mining methods to the spatio–temporal domain. Second, to demonstrate the usefulness of the extended methods and the derived knowledge in two promising LBS examples. Finally, to eliminate privacy concerns in connection with spatio–temporal data mining by devising systems for privacy–preserving location data collection and mining.   To this extent, Chapter 2 presents a general methodology, pivoting, to extend a popular data mining method, namely rule mining, to the spatio–temporal domain. By considering the characteristics of a number of real–world data sources, Chapter 2 also derives a taxonomy of spatio–temporal data, and demonstrates the usefulness of the rules that the extended spatio–temporal rule mining method can discover. In Chapter 4 the proposed spatio–temporal extension is applied to find long, sharable patterns in trajectories of moving objects. Empirical evaluations show that the extended method and its variants, using high–level SQL implementations, are effective tools for analyzing trajectories of moving objects. Real–world trajectory data about a large population of objects moving over extended periods within a limited geographical space is difficult to obtain. To aid the development in spatio–temporal data management and data mining, Chapter 3 develops a Spatio–Temporal ACTivity Simulator (ST–ACTS). ST–ACTS uses a number of real–world geo–statistical data sources and intuitive principles to effectively generate realistic spatio–temporal activities of mobile users.   Chapter 5 proposes an LBS in the transportation domain, namely cab–sharing. To deliver an effective service, a unique spatio–temporal grouping algorithm is presented and implemented as a sequence of SQL statements. Chapter 6 identifies ascalability bottleneck in the grouping algorithm. To eliminate the bottleneck, the chapter expresses the grouping algorithm as a continuous stream query in a data stream management system, and then devises simple but effective spatio–temporal partitioning methods for streams to parallelize the computation. Experimental results show that parallelization through adaptive partitioning methods leads to speed–ups of orders of magnitude without significantly effecting the quality of the grouping. Spatio–temporal stream partitioning is expected to be an effective method to scale computation–intensive spatial queries and spatial analysis methods for streams.   Location–Based Advertising (LBA), the delivery of relevant commercial information to mobile consumers, is considered to be one of the most promising business opportunities amongst LBSes. To this extent, Chapter 7 describes an LBA framework and an LBA database that can be used for the management of mobile ads. Using a simulated but realistic mobile consumer population and a set of mobile ads, the LBA database is used to estimate the capacity of the mobile advertising channel. The estimates show that the channel capacity is extremely large, which is evidence for a strong business case, but it also necessitates adequate user controls.   When data about users is collected and analyzed, privacy naturally becomes a concern. To eliminate the concerns, Chapter 8 first presents a grid–based framework in which location data is anonymized through spatio–temporal generalization, and then proposes a system for collecting and mining anonymous location data. Experimental results show that the privacy–preserving data mining component discovers patterns that, while probabilistic, are accurate enough to be useful for many LBSes.   To eliminate any uncertainty in the mining results, Chapter 9 proposes a system for collecting exact trajectories of moving objects in a privacy–preserving manner. In the proposed system there are no trusted components and anonymization is performed by the clients in a P2P network via data cloaking and data swapping. Realistic simulations show that under reasonable conditions and privacy/anonymity settings the proposed system is effective. / QC 20120215

Cross-media games are evolving as a new exciting platform for gaming where different devices are used to create a type of game play were a variant of devices, such as mobile phones and laptops are used. This thesis investigates the possibility of merging cross-media games into the domain of Mobile Learning to create a type of mobile learning game where collaboration becomes a vital part of the game play and style enhances collaboration between the users. By studying cross-media games, key features are captured and converted into requirements that are realised in a prototype that enables cross-media gaming with the intention of creating an environment in which learning could be supported. The development process of the prototype is described and evaluated in the thesis. The result presents a categorization of the key features for cross-media gaming and a prototype of a cross-media game. The thesis investigates which are the key technical features for creating cross-medial games for learning that can be identified for supporting the development process? The results presents a categorization of identified features along with potential future work based on the thesis. It is shown that features related to data sharing are highly prioritized and that certain features are absolutely required to enable cross-media gaming whilst others have less priority.

Android is a fast growing platform with a lot of users and applications on the market. In order to challenge the competition, a new software product should be designed carefully, conforming to the platform constraints and conveying to the user expectations. This research focuses on defining a suitable architecture design for the specific use case of interest, an Android application focused on location based data. The research process is backed up by a prototype application construction with features such as location based reminders and mobile communication with web services. Moreover, an analysis has been conducted on existing products with the proven quality, to extract information on current best practice implementations of several interesting features. Furthermore, the demand for targeting multiple platforms with the same application motivated a research on portability and reuse of code among different platforms. The constructed system is divided into a client-server pair. Opposite to the client (mobile) side, the server side analyzes the process of extending an existing architecture by integrating it with a web service project used for exchanging data with the mobile devices. Finally, the thesis is not strictly constrained to the given use case because it presents several general concepts of application design through architectural and design patterns.

The rise of mobile phones as the number one leading personal communication device make mobile phones very attractive for marketers, as they are always on, always with the consumer and always connected. Smartphones has the ability to update their location (thus the location of the consumer) by themselves. Through this an automatic location-dependent advertisement, triggered by the location of the mobile device, may be sent to any customer in a predetermined area. However, a current problem is how to not misuse this opportunity. For example, even though a consumer is in the nearby area of a store it does not mean that they are interested in receiving an offer. Consumers are also very keen on feeling in control of the access to their personal information. The purpose of this bachelor thesis is thus to investigate what attributes a location-based application may have to increase customer usage by enhancing, facilitating and developing the customers shopping behaviour. Theories used as a basis for investigation are marketing strategy, marketing innovation, direct marketing, mobile marketing (location-based marketing and permission-based marketing), consumer behaviour (customer value, attitudes and monetary- and non-monetary promotion). A deductive, qualitative research approach was chosen, semi-structured interviews and focus groups were conducted among students at the Linnaeus University in Växjö. The interviews regarded application attributes; the results obtained were used as a base for the focus group studies. In the analysis, the findings from the focus groups linked with theory outlined the attributes and how such an application should be designed. The most important categories are customisation and value, followed in descending order by functional, external, registration and privacy. Also concluded is how the customers shopping experience may be enhanced, facilitated and developed on the basis of these attributes. In the conclusion similarities and differences between the two focus groups were discussed and theoretical and managerial implications were outlined.

The aim of this study attempts to explore in which circumstance users would self-disclosure on Facebook with check-in behavior by considering extraversion and narcissism as psychological factors. Furthermore, in order to examine the relationships between different behaviors on Facebook, self-disclosure, exhibitionism and check-in intensity, this study used exhibitionism as the mediator to discuss if users¡¦ cognition of exhibitionism toward check-in would influence their attempt on check-in and clarify the attributes which make users behave in this way. Finally, a framework is proposed based on the results. Purposive sampling was used in the study. Questionnaire data were collected by the Internet and totally received 523 valid respondents. The study used LISREL structural equation models to test goodness of fit, validity, and furthermore adopted full model to examine the hypotheses. The results showed that the extraversion has an impact on the extent of self-disclosure on Facebook; however, narcissism does not have a significant effect on self-disclosure. As for the relationship between self-disclosure, exhibitionism and check-in intensity, self-disclosure would directly influence the attempts at check-in intensity. On the other hand, exhibitionism would also make self-disclosure have an impact on check-in intensity as a partial mediator.

With the ubiquity of mobile devices, there has been increased interest in determining how they can be used with location-based services. These types of services work best when the device has the ability to sense its location frequently, while still maintaining enough battery life to carry out its normal daily functions. Since the life of the battery on a mobile device is already so limited, ways of preserving that energy has become an important issue. The goal of this thesis is to demonstrate that Bluetooth can assist in providing energy efficient mobile device localization. This goal is achieved through a proposed Bluetooth Location Service Discovery framework which provides an API that can be incorporated into third party applications. The API allows BlackBerry devices to use surrounding Bluetooth devices in order to make a prediction about its current location. Predictions are completed with the assistance of the K-Nearest Neighbour data mining algorithm, and can be used as an alternative to invoking the GPS. The results obtained through experiments demonstrate that the results are comparable to those obtained with GPS.