An integrated mobile content recommendation system

Many features have been added to mobile devices to assist the user's information consumption. However, there are limitations due to information overload on the devices, hardware usability and capacity. As a result, content filtering in a mobile recommendation system plays a vital role in the solution to this problem. A system that utilises content filtering can recommend content which matches a user's needs based on user preferences with a higher accuracy rate. However, mobile content recommendation systems have problems and limitations related to cold start and sparsity. The problems can be viewed as first time connection and first content rating for non-interactive recommendation systems where information is insufficient to predict mobile content which will match with a user's needs. In addition, how to find relevant items for the content recommendation system which are related to a user's profile is also a concern. An integrated model that combines the user group identification and mobile content filtering for mobile content recommendation was proposed in this study in order to address the current limitations of the mobile content recommendation system. The model enhances the system by finding the relevant content items that match with a user's needs based on the user's profile. A prototype of the client-side user profile modelling is also developed to demonstrate the concept. The integrated model applies clustering techniques to determine groups of users. The content filtering implemented classification techniques to predict the top content items. After that, an adaptive association rules technique was performed to find relevant content items. These approaches can help to build the integrated model. Experimental results have demonstrated that the proposed integrated model performs better than the comparable techniques such as association rules and collaborative filtering. These techniques have been used in several recommendation systems. The integrated model performed better in terms of finding relevant content items which obtained higher accuracy rate of content prediction and predicted successful recommended relevant content measured by recommendation metrics. The model also performed better in terms of rules generation and content recommendation generation. Verification of the proposed model was based on real world practical data. A prototype mobile content recommendation system with client-side user profile has been developed to handle the revisiting user issue. In addition, context information, such as time-of-day and time-of-week, could also be used to enhance the system by recommending the related content to users during different time periods. Finally, it was shown that the proposed method implemented fewer rules to generate recommendation for mobile content users and it took less processing time. This seems to overcome the problems of first time connection and first content rating for non-interactive recommendation systems

Using contextual information to understand searching and browsing behavior

There is great imbalance in the richness of information on the web and the succinctness and poverty of search requests of web users, making their queries only a partial description of the underlying complex information needs. Finding ways to better leverage contextual information and make search context-aware holds the promise to dramatically improve the search experience of users. We conducted a series of studies to discover, model and utilize contextual information in order to understand and improve users' searching and browsing behavior on the web. Our results capture important aspects of context under the realistic conditions of different online search services, aiming to ensure that our scientific insights and solutions transfer to the operational settings of real world applications

Field lab Jeronimo Martins: optimization of retail operations - a cluster-based approach to market basket analysis

In the context of retail analytics, market basket analysis serves as a powerful technique to extract valuable knowledge about consumer preferences and shopping habits. Through its application to a Portuguese retailer, the following study examines purchase transaction data and clusters it based on the product categories in consumers’ baskets. With the goal of mining product relationships, this study compares a heuristic and an association rule-based approach for a cluster-based identification of product substitutes and complements. The paper concludes that for finding substitutes, the heuristic fares the best results. For the discovery of product complementarity, an association rule learning-based approach is suited best. Beyond its theoretical contribution, the insights gained through the analyses are utilized to increase customer satisfaction and sales by providing recommendations on managerial decisions, ranging from determining the timing of product promotions, possible improvements to the store’s design, informing product placement decisions, to suggestions regarding customer communication

HYPERLINK NETWORK SYSTEM AND IMAGE OF GLOBAL CITIES: WEBPAGES AND THEIR CONTENTS

A distinctive trend of globalization research is a conceptual expansion that mirrors the penetration of globalization in various aspects of life. The World Wide Web has become the ultimate platform to create and disseminate information in this era of globalization. Although the importance of web-based information is widely acknowledged, the use of this information in global city research is not significant yet. Therefore, the purpose of this research is to extend the concept of globalization to the efficiency of information networks and the thematic dimensionality of the conveyed images from webpages. To this end, 264 global and globalizing cities are selected. The city hyperlink networks are constructed from the web crawling results of each city, and hyperlink network analysis measures the effectiveness of these hyperlink networks. The textual contents are also extracted from the crawled webpages, and the thematic dimensionality of the textual contents is measured by quantified content analysis and multidimensional scaling. The efficiency of the hyperlink network in information flow is confirmed to be a new consideration that shapes the globality of cities. The cities with high efficiency of connections have faster and easier access, which means better structure for city image formation. Specifically, social networking websites are the center of this information flow. This means that social interactions on the Web play a crucial role to form the images of cities. Apart from the positivity and the negativity of the city image, the dimensionality of cities on the thematic space denotes how they are expressed, discussed, and shared on the Web. The image status based on dimensions of globalization is an important starting point to city branding. It is concluded that a research framework handling information networks and images simultaneously deepens the understanding of how the structure and the contents on the Web affect the formation and maintenance of global city networks. Overall, this research demonstrates the usefulness of information networks and images of cities on the Web to overcome data inconsistency and scarcity in global city research

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Modeling Relationships Among Affective Measures of Food Choice: Acceptance, Emotions And Satisfaction

The importance of ascertaining holistic product and consumer understanding beyond liking in the product development process cannot be overstated. This research investigated the role of attribute performance on satisfaction in explaining the relationship between food-evoked emotions and sensory preferences, and examined factors influencing the sensory-emotion profile of food products. In the first phase of this research, a series of consumer studies were conducted using eggs as a test product. First, the extent to which critical product attributes contribute to the satisfaction of quality requirements and purchase intent was determined using Kano modeling concepts. The emotional profile of the product was then examined in attribute presence and absence conditions to evaluate impact of egg quality types. Subsequently, the data were analyzed to elucidate relationships between emotions, satisfaction performance measures and product acceptability. For the expansive aspects of intrinsic, extrinsic, aesthetic, expedient and wholesome characteristics influencing purchase decision of eggs, 8 elements were identified as must-be, 1 attractive, 1 one-dimensional, and 10 indifferent Kano attributes. Attribute absence rather than presence evoked greater consumer discriminating emotions, and emotions and acceptability were more correlated for attribute absence than presence. Emotion and attribute satisfaction performance scores were better predictors of liking in combination than alone. However, emotions in attribute absence outperformed that in its presence, reflecting impact of deeper emotional conceptualizations in attribute absence being a better predictor of liking. Associations were found between Kano attributes and positive emotions. Attractive Kano-related attributes were distinctly drivers of liking, separate from both positive and negative emotions. No evidence of moderating effects of satisfaction performance of expedient egg attributes on the relationship between emotions and liking was found. In the second phase of this research, the relative effects of color and labeling cues on sensory perception, emotional responses and the sensory-emotion space were evaluated using sweeteners as a food model. Results demonstrated additive effects of color and labeling cues on flavor perception and emotions, contrary to significant interactions on their sensory-emotion profile. Identified associations between attribute performance on consumer satisfaction, emotions and acceptability in this research offer new insights on food-evoked emotions in product development

2017 Annual Research Symposium Abstract Book

2017 annual volume of abstracts for science research projects conducted by students at Trinity College

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security

Semantic Interaction in Web-based Retrieval Systems : Adopting Semantic Web Technologies and Social Networking Paradigms for Interacting with Semi-structured Web Data

Existing web retrieval models for exploration and interaction with web data do not take into account semantic information, nor do they allow for new forms of interaction by employing meaningful interaction and navigation metaphors in 2D/3D. This thesis researches means for introducing a semantic dimension into the search and exploration process of web content to enable a significantly positive user experience. Therefore, an inherently dynamic view beyond single concepts and models from semantic information processing, information extraction and human-machine interaction is adopted. Essential tasks for semantic interaction such as semantic annotation, semantic mediation and semantic human-computer interaction were identified and elaborated for two general application scenarios in web retrieval: Web-based Question Answering in a knowledge-based dialogue system and semantic exploration of information spaces in 2D/3D