4 research outputs found

    How to monitor and generate intelligence for a DMO from online reviews

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceSocial media and customer review websites have changed the way the tourism sector is managed. Social media has become a new source of information, due to the large amount of UGC / e-Wom generated by consumers An information that is "available" but at the same time noisy and of great volume, which makes it difficult to access and analyze. This study investigates and verifies the possibility of using data present in content reviews of a Content Web Site Review - TripAdivsor - to generate actionable information for a Destination Management Organization. With a focus on negative reviews, tourist attractions of Lisbon and using the “R code” and its packages, the study shows that with the correct technique chosen and the action of an intelligence analyst, data can be extracted and provide substrate for actions, strategy and intelligence generation – which is Social Media Intelligence. The findings prove that the flood of web 2.0 data can serve as a source of intelligence for the Destination Management Organization (DMO). By monitoring sites like TripAdvisor, a DMO can hear what tourists talk about attractions and thereby generate insights for intelligence and strategy actions. A DMO can even, analyzing this data, make your attractions more desirable, and even act in adverse situations, reducing risky situations

    A Context-Aware Model to Improve Usability of Information Display on Smartphone Apps for Emerging Users

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    Smartphones have become a reliable technology for accessing information and services in rural communities. Mobile applications, such as social media and news apps running on smartphones, are no longer exclusively utilised by users in developed communities. Mobile applications are accessed in highly contextualised environments. This paper discusses a context-aware model that was implemented to improve the usability of information presented on smartphone applications for emerging users. User evaluation was conducted within a remote area in South Africa with a sample of users, most of whom did not have prior experience in using computer applications. The results of the evaluation present empirical evidence that the model can improve the usefulness of mobile applications and their adoption in rural areas by emerging users who primarily rely on smartphones for accessing a variety of information sources and services. The findings can be utilised as a blueprint for implementing sustainable mobile interventions for emerging users

    No less than a women: improving breast cancer detection & diagnosis

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    Breasts, being the ultimate symbol of femininity, make breast cancer one of the most traumatic events any woman could ever face. Perhaps it is this sense of pride in these attributes that makes many women reluctant to discuss and share their experiences with breast cancer. Many may feel that their absolute core identity has been shaken, making them less than a woman. The fear and stigma attached to this disease are currently among the major difficulties faced by healthcare providers in convincing women to effectively manage their breast disease. It may leave women feeling isolated and as a result, withdrawing from society and even life- making them feel less than a woman. Beyond the stigma and mental anguish there is also the tremendous stress of going through a number of surgeries, chemotherapies and radiation therapies, with the risk of treatment failure and recurrence always at the back of their minds. Fortunately various studies confirm that early breast cancer detection saves lives, reduces medical treatments and costs, and ultimately, gives one hope for a better future. The availability of effective screening reduces the mortality from breast cancer by up to 50%. Most women will be lucky enough to never develop breast cancer, but for the many of those who do, their lives may be saved by advanced detection. Currently, breast cancer detected at an early stage can be treated appropriately, with most being cured. The role of a health care provider is therefore extremely important, in counselling and motivating women to overcome their fears and come forward for regular examinations. The role of a radiologist is equally important in synergizing imaging modalities towards achieving the best of medical care for the public. These are some of the ways to help and support in the management of the disease and in making the ladies feel no less than a woman. In order to reach a superior level in early detection and diagnosis of breast cancer, our research team studied various methods to overcome some of the limitations in breast imaging. These methods include Computer Aided Diagnosis techniques involving various existing imaging modalities such as mammogram, tomosynthesis, breast ultrasound, computed tomography laser mammography (CTLM) and thermography of the breast. More rewarding research on newer imaging devices includes the ultra-wide band (UWB) imaging of the breast. Recent usage of a computational model involving Monte Carlo Simulation for early breast cancer detection using wire mesh collimator gamma camera in scintimammography is also gaining interest amongst clinicians

    A context-aware model to improve usability of information presented on mobile devices

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    Online information access on mobile devices is increasing as a result of the growth in the use of Internet-enabled handheld (or pocket-size) devices. The combined influence of recent enabling technologies such as Web 2.0, mobile app stores and improved wireless networks have driven the increase in online applications that allow users to access various types of information on mobile devices regardless of time and location. Examples of such applications (usually shortened to app) include: social media, such as FacebookTM App and TwitterTM App, banking applications such as (Standard Bank South Africa)TM Mobile Banking App and First National Bank (FNB) BankingTM App, and news application such as news 24TM App and BBCTM News App. Online businesses involved in buying, selling and business transaction processing activities via the Internet have exploited the opportunity to extend electronic commerce (e-commerce) initiatives into mobile commerce (m-commerce). Online businesses that interact with end user customers implement business to consumer (B2C) m-commerce applications that enable customers to access and browse product catalogue information on mobile devices, anytime, anywhere. Customers accessing electronic product catalogue information on a mobile device face a number of challenges such as a long list of products presented on a small screen and a longer information download time. These challenges mainly originate from the limiting and dynamic nature of the mobile apps operating environment, for example, dynamic location, bandwidth fluctuations and, diverse and limited device features, collectively referred to as context. The goal of this research was to design and implement a context-aware model that can be incorporated into an m-commerce application in order to improve the presentation of product catalogue information on m-commerce storefronts. The motivation for selecting product catalogue is prompted by literature which indicates that improved presentation of information in m-commerce (and e-commerce) applications has a positive impact on usability of the websites. Usable m-commerce (and e-commerce) websites improve efficiency in consumer behaviour that impacts sales, profits and business growth. The context-aware model aimed at collecting context information within the user environment and utilising it to determine optimal retrieval and presentation of product catalogue in m-commerce. An integrated logical context sensor and Mathematical algorithms were implemented in the context-aware model. The integrated logical context sensor was responsible for the collection of different types of predetermined context information such as device specification or capabilities, connection bandwidth, location and time of the day as well as the user profile. The algorithms transformed the collected context information into usable formats and enabled optimal retrieval and presentation of product catalogue data on a specific mobile device. Open-source implementation tools were utilised to implement components of the model including: HTML5, PhP, JavaScript and MySQL database. The context-aware model was incorporated into an existing m-commerce application. Two user evaluation studies were conducted during the course of the research. The first evaluation was to evaluate the accuracy of information collected by the context sensor component of the model. This survey was conducted with a sample of 30 users from different countries across the world. In-between the context sensor and main evaluation surveys, a pilot study was conducted with a sample of 19 users with great experience in mobile application development and use from SAP Next Business and Technology, Africa. Finally an overall user evaluation study was conducted with a sample of 30 users from a remote area called Kgautswane in Limpopo Province, South Africa. The results obtained indicate that the context-aware model was able to determine accurate context information in real-time and effectively determine how much product information should be retrieved and how the information should be presented on a mobile device interface. Two main contributions emerged from the research, first the research contributed to the field of mobile Human Computer Interaction. During the research, techniques of evaluating and improving usability of mobile applications were demonstrated. Secondly, the research made a significant contribution to the upcoming field of context-aware computing. The research brought clarity with regard to context-aware computing which is lacking in existing, current research despite the field’s proven impact of improving usability of applications. Researchers can utilise contributions made in this research to develop further techniques and usable context-aware solutions
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