Colour-based image retrieval algorithms based on compact colour descriptors and dominant colour-based indexing methods

Content based image retrieval (CBIR) is reported as one of the most active research areas in the last two decades, but it is still young. Three CBIR’s performance problem in this study is inaccuracy of image retrieval, high complexity of feature extraction, and degradation of image retrieval after database indexing. This situation led to discrepancies to be applied on limited-resources devices (such as mobile devices). Therefore, the main objective of this thesis is to improve performance of CBIR. Images’ Dominant Colours (DCs) is selected as the key contributor for this purpose due to its compact property and its compatibility with the human visual system. Semantic image retrieval is proposed to solve retrieval inaccuracy problem by concentrating on the images’ objects. The effect of image background is reduced to provide more focus on the object by setting weights to the object and the background DCs. The accuracy improvement ratio is raised up to 50% over the compared methods. Weighting DCs framework is proposed to generalize this technique where it is demonstrated by applying it on many colour descriptors. For reducing high complexity of colour Correlogram in terms of computations and memory space, compact representation of Correlogram is proposed. Additionally, similarity measure of an existing DC-based Correlogram is adapted to improve its accuracy. Both methods are incorporated to produce promising colour descriptor in terms of time and memory space complexity. As a result, the accuracy is increased up to 30% over the existing methods and the memory space is decreased to less than 10% of its original space. Converting the abundance of colours into a few DCs framework is proposed to generalize DCs concept. In addition, two DC-based indexing techniques are proposed to overcome time problem, by using RGB and perceptual LUV colour spaces. Both methods reduce the search space to less than 25% of the database size with preserving the same accuracy

A semantic methodology for (un)structured digital evidences analysis

Nowadays, more than ever, digital forensics activities are involved in any criminal, civil or military investigation and represent a fundamental tool to support cyber-security. Investigators use a variety of techniques and proprietary software forensic applications to examine the copy of digital devices, searching hidden, deleted, encrypted, or damaged files or folders. Any evidence found is carefully analysed and documented in a "finding report" in preparation for legal proceedings that involve discovery, depositions, or actual litigation. The aim is to discover and analyse patterns of fraudulent activities. In this work, a new methodology is proposed to support investigators during the analysis process, correlating evidences found through different forensic tools. The methodology was implemented through a system able to add semantic assertion to data generated by forensics tools during extraction processes. These assertions enable more effective access to relevant information and enhanced retrieval and reasoning capabilities

AXMEDIS 2008

The AXMEDIS International Conference series aims to explore all subjects and topics related to cross-media and digital-media content production, processing, management, standards, representation, sharing, protection and rights management, to address the latest developments and future trends of the technologies and their applications, impacts and exploitation. The AXMEDIS events offer venues for exchanging concepts, requirements, prototypes, research ideas, and findings which could contribute to academic research and also benefit business and industrial communities. In the Internet as well as in the digital era, cross-media production and distribution represent key developments and innovations that are fostered by emergent technologies to ensure better value for money while optimising productivity and market coverage

AI for social good: social media mining of migration discourse

The number of international migrants has steadily increased over the years, and it has become one of the pressing issues in today’s globalized world. Our bibliometric review of around 400 articles on Scopus platform indicates an increased interest in migration-related research in recent times but the extant research is scattered at best. AI-based opinion mining research has predominantly noted negative sentiments across various social media platforms. Additionally, we note that prior studies have mostly considered social media data in the context of a particular event or a specific context. These studies offered a nuanced view of the societal opinions regarding that specific event, but this approach might miss the forest for the trees. Hence, this dissertation makes an attempt to go beyond simplistic opinion mining to identify various latent themes of migrant-related social media discourse. The first essay draws insights from the social psychology literature to investigate two facets of Twitter discourse, i.e., perceptions about migrants and behaviors toward migrants. We identified two prevailing perceptions (i.e., sympathy and antipathy) and two dominant behaviors (i.e., solidarity and animosity) of social media users toward migrants. Additionally, this essay has also fine-tuned the binary hate speech detection task, specifically in the context of migrants, by highlighting the granular differences between the perceptual and behavioral aspects of hate speech. The second essay investigates the journey of migrants or refugees from their home to the host country. We draw insights from Gennep's seminal book, i.e., Les Rites de Passage, to identify four phases of their journey: Arrival of Refugees, Temporal stay at Asylums, Rehabilitation, and Integration of Refugees into the host nation. We consider multimodal tweets for this essay. We find that our proposed theoretical framework was relevant for the 2022 Ukrainian refugee crisis – as a use-case. Our third essay points out that a limited sample of annotated data does not provide insights regarding the prevailing societal-level opinions. Hence, this essay employs unsupervised approaches on large-scale societal datasets to explore the prevailing societal-level sentiments on YouTube platform. Specifically, it probes whether negative comments about migrants get endorsed by other users. If yes, does it depend on who the migrants are – especially if they are cultural others? To address these questions, we consider two datasets: YouTube comments before the 2022 Ukrainian refugee crisis, and during the crisis. Second dataset confirms the Cultural Us hypothesis, and our findings are inconclusive for the first dataset. Our final or fourth essay probes social integration of migrants. The first part of this essay probed the unheard and faint voices of migrants to understand their struggle to settle down in the host economy. The second part of this chapter explored the viability of social media platforms as a viable alternative to expensive commercial job portals for vulnerable migrants. Finally, in our concluding chapter, we elucidated the potential of explainable AI, and briefly pointed out the inherent biases of transformer-based models in the context of migrant-related discourse. To sum up, the importance of migration was recognized as one of the essential topics in the United Nation’s Sustainable Development Goals (SDGs). Thus, this dissertation has attempted to make an incremental contribution to the AI for Social Good discourse

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Sports sponsorship and the impact on a brand's purchasing intention and recommendation: Red Bull, more than wings

Sponsorship has proven to be a fast-flourishing marketing tool. Its main essence is, in the companies' perspective, to effectively promote their products and services. Therefore, over the years, companies have begun to behold and consider this tool as a massive gateway for a successful strategical long-term plan. Previous sponsorship studies, have instigated to examine its concept on multiple situations and the implications they entail, but often lack new effective measures and approaches. Hence, the purpose of this investigation is to better understand and scrutinize the effects of Sports Sponsorship - its Awareness, Perceived Quality and Image - on Brand Equity variables, in particular, on Brand Image, Brand Awareness, Brand Loyalty and Perceived Brand Quality. Consequently, with that in mind, there is an examination of the effect/influence on the consumer's Brand Purchasing Intention and Brand Recommendation. Moreover, Red Bull, is used as a main reference. The energy drinks' company was placed on a Sports Sponsorship context, with 3 main sports highlighted (Football/Soccer, Air Racing and Formula 1). The respondents (from a diverse age range), were asked several questions considering Sponsorship and Brand Equity's variables and, their a-posteriori Brand Purchasing Intention and Recommendation - always heeding the Brand´s Sports Sponsorship they consider to be the most important. The results gathered by the following research propose that the presence of a Sports Sponsorship initiative brings no direct influence on a Brand's Purchasing Intention and Recommendation. In addition, Perceived Brand Quality affects both final variables, whereas Brand Awareness impacts none.O Patrocínio tem-se revelado uma ferramenta de rápido crescimento, tendo como principal objetivo, do ponto de vista das empresas, a promoção eficaz dos seus produtos e serviços. Com o passar dos anos, as empresas começaram a reconhecer esta ferramenta como um portal sólido para o sucesso estratégico, no longo prazo. Estudos prévios sobre o Patrocínio têm exibido detalhadas análises, sob diversas situações, todavia, sem um fio condutor eficaz. Portanto, o objetivo desta investigação consiste num melhor escrutínio dos efeitos do Patrocínio no Desporto - a sua Consciência, Qualidade Percetível e Imagem - nas variáveis referentes ao Valor da Marca, mais exatamente, a Imagem da Marca, a Consciência da Marca, a Lealdade à Marca e a Qualidade Percetível da Marca. Consequentemente, é examinado o efeito na Intenção de Compra e Recomendação da Marca. Para além disso, Red Bull, é usada como referência principal de estudo. A empresa de bebidas energéticas foi colocada no contexto dos seus patrocínios desportivos, com realce a três (Futebol, "Air Racing" e Formula 1). Os inquiridos foram questionados relativamente às variáveis de Patrocínio e Valor da Marca, como também, à Intenção de Compra e Recomendação da Marca – considerando o Patrocínio de Desporto por eles considerado como o mais importante para a Marca. Os resultados recolhidos da investigação apontam para que as iniciativas de Patrocínio no Desporto não tenham uma influência direta na Intenção de Compra e Recomendação da Marca. Ademais, a Qualidade Percetível da Marca produz um efeito direto nas duas variáveis dependentes, ao invés da Consciência à Marca

Minds Online: The Interface between Web Science, Cognitive Science, and the Philosophy of Mind

Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis they place on forces and factors that reside at the level of agent–world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind