Mining health knowledge graph for health risk prediction

Nowadays classification models have been widely adopted in healthcare, aiming at supporting practitioners for disease diagnosis and human error reduction. The challenge is utilising effective methods to mine real-world data in the medical domain, as many different models have been proposed with varying results. A large number of researchers focus on the diversity problem of real-time data sets in classification models. Some previous works developed methods comprising of homogeneous graphs for knowledge representation and then knowledge discovery. However, such approaches are weak in discovering different relationships among elements. In this paper, we propose an innovative classification model for knowledge discovery from patients’ personal health repositories. The model discovers medical domain knowledge from the massive data in the National Health and Nutrition Examination Survey (NHANES). The knowledge is conceptualised in a heterogeneous knowledge graph. On the basis of the model, an innovative method is developed to help uncover potential diseases suffered by people and, furthermore, to classify patients’ health risk. The proposed model is evaluated by comparison to a baseline model also built on the NHANES data set in an empirical experiment. The performance of proposed model is promising. The paper makes significant contributions to the advancement of knowledge in data mining with an innovative classification model specifically crafted for domain-based data. In addition, by accessing the patterns of various observations, the research contributes to the work of practitioners by providing a multifaceted understanding of individual and public health

Recherche d'Information Sociale et Recommandation: Etat d'art et travaux futurs

International audienceThe explosion of web 2.0 and social networks has created an enormous and rewarding source of information that has motivated researchers in different fields to exploit it. Our work revolves around the issue of access and identification of social information and their use in building a user profile enriched with a social dimension, and operating in a process of personalization and recommendation. We study several approaches of Social IR (Information Retrieval), distinguished by the type of incorporated social information. We also study various social recommendation approaches classified by the type of recommendation. We then present a study of techniques for modeling the social user profile dimension, followed by a critical discussion. Thus, we propose our social recommendation approach integrating an advanced social user profile model.L’explosion du web 2.0 et des réseaux sociaux a crée une source d’information énorme et enrichissante qui a motivé les chercheurs dans différents domaines à l’exploiter. Notre travail s’articule autour de la problématique d’accès et d’identification des informations sociales et leur exploitation dans la construction d’un profil utilisateur enrichi d’une dimension sociale, et son exploitation dans un processus de personnalisation et de recommandation. Nous étudions différentes approches sociales de RI (Recherche d’Information), distinguées par le type d’informations sociales incorporées. Nous étudions également diverses approches de recommandation sociale classées par le type de recommandation. Nous exposons ensuite une étude des techniques de modélisation de la dimension sociale du profil utilisateur, suivie par une discussion critique. Ainsi, nous présentons notre approche de recommandation sociale proposée intégrant un modèle avancé de profil utilisateur social

On relational learning and discovery in social networks: a survey

The social networking scene has evolved tremendously over the years. It has grown in relational complexities that extend a vast presence onto popular social media platforms on the internet. With the advance of sentimental computing and social complexity, relationships which were once thought to be simple have now become multi-dimensional and widespread in the online scene. This explosion in the online social scene has attracted much research attention. The main aims of this work revolve around the knowledge discovery and datamining processes of these feature-rich relations. In this paper, we provide a survey of relational learning and discovery through popular social analysis of different structure types which are integral to applications within the emerging field of sentimental and affective computing. It is hoped that this contribution will add to the clarity of how social networks are analyzed with the latest groundbreaking methods and provide certain directions for future improvements

Marketing Strategies of Successful Coffee Shop Owners

Failure is an issue with small businesses globally; some owners of small businesses lack the knowledge of business administration and marketing strategies necessary to help ensure success. The purpose of this multiple case study was to explore what marketing strategies some coffee shop owners use to sustain business operations during the first 5 years of operation. The targeted population consisted of 5 coffee shop owners in Arkansas who successfully implemented marketing strategies to sustain business operations during the first 5 years of operation. Goldsmith\u27s 8Ps of marketing mix was the conceptual framework used in the study. Data were collected from semistructured interviews and a review of publicly available data and company websites. Data were analyzed using the principles of the content analysis method, which included identifying codes and themes. Findings indicated owners of successful coffee shops were actively engaged in the day-to-day business operations and in the community; provided premium products; used social media for marketing, promotion, and branding; used competitive pricing; were precise about the location; provided exceptional customer service and personalization, and had points of marketing differentiation to promote their brand. The implications of this study for positive social change include the potential to support the welfare of the citizens of Arkansas, and owners of coffee shops across the United States that could provide independent coffee shop owners with marketing strategies necessary to sustain business operations, contribute to new job creation and regional economic sustainability

Design of a horizontal cooperation architecture based on metamodels, focused on electronic commerce platforms for mobile devices: case study of smes in the textile sector in Bogotá

Este artículo evidencia una arquitectura de cooperación horizontal para facilitar el proceso de transporte de mercancía en plataformas de comercio electrónico. Para ello se generó una taxonomía, un modelo semántico, una ontología que permita modelar dicha logística electrónica, después se utilizará la ontología generada para crear un metamodelo y luego un DSL basado en este, finalmente con MDE y aplicando transformación de los datos por medio de QVT, se logrará un modelo de datos interoperable para varias plataformas de comercio electrónico, en el que los operadores logísticos puedan ver la mercancía de forma transversal.The main objective of this thesis is to propose horizontal cooperation architecture to facilitate the shipping process in e-commerce platforms. First we will generate a taxonomy, a semantic model, an ontology that allows simulate that e-logistics, use the ontology to create a Metamodel and later an DSL, finally with MDE and applying data transformation using QVT, it will achieve a model of interoperable data e-commerce platforms, and the logistics operators will see the comodity transversely

Strategies for Small Business Sustainability Beyond 5 Years in New Restaurant Industry

More than half of small businesses in the United States are unsustainable within the first five years of existence. Small business owners who do not implement successful and sustainable strategies are at a high risk of failure. Grounded in the resource-based view theory, the purpose of this qualitative multiple case study was to explore strategies that some small restaurant owners use to sustain business beyond five years. The participants included three small business owners in Connecticut who have been in business for five years. Data were collected from semistructured interviews, company websites, and company documents. Yin’s 5-step thematic analysis was used to analyze the data. Five major themes emerged: financial capital resources; education, technical experience, and skills; challenges implementing technology and social media strategies; customer loyalty, customer retention, and offering quality services and resource-based strategic planning, flexibility, and seasonality. A key recommendation is that small business owners identify useful resources and effective business strategies to ensure their long-term sustainability. The implications for positive social change include the potential for small business owners to serve as leaders in furthering sustainable economic prosperity that benefits their communities. Further positive implications include the potential to create new jobs

Leveraging Internal Resources for Business Sustainability in Independent Quick-Service Restaurants

Quick-service restaurant owners who fail to apply effective business strategies could risk business closure within the first 5 years of operations. The purpose of this multiple case study was to explore effective strategies that independent quick-service restaurant owners used to sustain business longer than the first 5 years. Resource-based theory was the conceptual framework for this study. Data were collected via semistructured interviews with 6 owners of independent quick-service restaurants in the southern region of the United States who sustained their businesses longer than the first 5 years, and from the review of business documents pertaining to sustainability. Data were also collected using business artifacts such as job descriptions, menus, websites, social media platforms, and business licenses, and analyzed using methodological triangulation. Member checking was used to help ensure reliability and validity of the interpretations. Six key themes emerged from the data: organization value, customer required excellence, financial perspective, human assets, physical operating materials, and technological prowess. The 6 themes aligned with the 5 types of internal resources established in the conceptual framework. The implications of this study for positive social change include the potential to support the welfare of the local citizens and owners of quick-service restaurants across the United States by providing strategies necessary to increase business survival rates, improve job sustainability, and encourage job creation