BlogForever D3.2: Interoperability Prospects

This report evaluates the interoperability prospects of the BlogForever platform. Therefore, existing interoperability models are reviewed, a Delphi study to identify crucial aspects for the interoperability of web archives and digital libraries is conducted, technical interoperability standards and protocols are reviewed regarding their relevance for BlogForever, a simple approach to consider interoperability in specific usage scenarios is proposed, and a tangible approach to develop a succession plan that would allow a reliable transfer of content from the current digital archive to other digital repositories is presented

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Cognition and the Web

Empirical research related to the Web has typically focused on its impact to social relationships and wider society; however, the cognitive impact of the Web is also an increasing focus of scientific interest and research attention. In this paper, I attempt to provide an overview of what I see as the important issues in the debate regarding the relationship between human cognition and the Web. I argue that the Web is potentially poised to transform our cognitive and epistemic profiles, but that in order to understand the nature of this influence we need to countenance a position that factors in the available scientific evidence, the changing nature of our interaction with the Web, and the possibility that many of our everyday cognitive achievements rely on complex webs of social and technological scaffolding. I review the literature relating to the cognitive effects of current Web technology, and I attempt to anticipate the cognitive impact of next-generation technologies, such as Web-based augmented reality systems and the transition to data-centric modes of information representation. I suggest that additional work is required to more fully understand the cognitive impact of both current and future Web technologies, and I identify some of the issues for future scientific work in this area. Given that recent scientific effort around the Web has coalesced into a new scientific discipline, namely that of Web Science, I suggest that many of the issues related to cognition and the Web could form part of the emerging Web Science research agenda

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

Large Language Models for Information Retrieval: A Survey

As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve as components of dialogue, question-answering, and recommender systems. The trajectory of IR has evolved dynamically from its origins in term-based methods to its integration with advanced neural models. While the neural models excel at capturing complex contextual signals and semantic nuances, thereby reshaping the IR landscape, they still face challenges such as data scarcity, interpretability, and the generation of contextually plausible yet potentially inaccurate responses. This evolution requires a combination of both traditional methods (such as term-based sparse retrieval methods with rapid response) and modern neural architectures (such as language models with powerful language understanding capacity). Meanwhile, the emergence of large language models (LLMs), typified by ChatGPT and GPT-4, has revolutionized natural language processing due to their remarkable language understanding, generation, generalization, and reasoning abilities. Consequently, recent research has sought to leverage LLMs to improve IR systems. Given the rapid evolution of this research trajectory, it is necessary to consolidate existing methodologies and provide nuanced insights through a comprehensive overview. In this survey, we delve into the confluence of LLMs and IR systems, including crucial aspects such as query rewriters, retrievers, rerankers, and readers. Additionally, we explore promising directions within this expanding field

ChatGPT recommendation system for retail shops

The rapid growth of e-commerce platforms has emphasized the significance of personalized recommendation systems in enhancing user engagement and satisfaction. This dissertation presents the development and evaluation of an innovative Product Recommendation System that leverages advanced Artificial Intelligence (AI) techniques to provide tailored product suggestions. The primary objective is to create a user-centric experience by integrating an AI assistant, enabling natural and interactive interactions. Through a comprehensive survey conducted to understand customer behaviours while purchasing products using AI, the study aims to assess the system's effectiveness in delivering accurate recommendations and providing a seamless purchasing experience. This document contributes to the field by showcasing the practical implementation of AI-driven recommendation systems, highlighting their potential to transform e-commerce interactions.O rápido crescimento das plataformas de comércio eletrónico enfatizou a importância dos sistemas de recomendação personalizados para aumentar o envolvimento e a satisfação dos utilizadores. Esta tese apresenta o desenvolvimento e avaliação de um Sistema de Recomendação de Produtos inovador que utiliza técnicas avançadas de Inteligência Artificial (IA) para fornecer sugestões de produtos personalizadas. O objetivo principal é criar uma experiência centrada no usuário, integrando um assistente de IA, permitindo interações naturais e interativas. Através de uma pesquisa abrangente realizada para compreender o comportamento dos clientes durante a compra de produtos usando IA, o estudo visa avaliar a eficácia do sistema na entrega de recomendações precisas e no fornecimento de uma experiência de compra perfeita. Este documento contribui para a área ao mostrar a implementação prática de sistemas de recomendação baseados em IA, destacando o seu potencial para transformar as interações de comércio eletrónico

Generative Artificial Intelligence for Software Engineering -- A Research Agenda

Generative Artificial Intelligence (GenAI) tools have become increasingly prevalent in software development, offering assistance to various managerial and technical project activities. Notable examples of these tools include OpenAIs ChatGPT, GitHub Copilot, and Amazon CodeWhisperer. Although many recent publications have explored and evaluated the application of GenAI, a comprehensive understanding of the current development, applications, limitations, and open challenges remains unclear to many. Particularly, we do not have an overall picture of the current state of GenAI technology in practical software engineering usage scenarios. We conducted a literature review and focus groups for a duration of five months to develop a research agenda on GenAI for Software Engineering. We identified 78 open Research Questions (RQs) in 11 areas of Software Engineering. Our results show that it is possible to explore the adoption of GenAI in partial automation and support decision-making in all software development activities. While the current literature is skewed toward software implementation, quality assurance and software maintenance, other areas, such as requirements engineering, software design, and software engineering education, would need further research attention. Common considerations when implementing GenAI include industry-level assessment, dependability and accuracy, data accessibility, transparency, and sustainability aspects associated with the technology. GenAI is bringing significant changes to the field of software engineering. Nevertheless, the state of research on the topic still remains immature. We believe that this research agenda holds significance and practical value for informing both researchers and practitioners about current applications and guiding future research