Hasil untuk "Bibliography. Library science. Information resources"

S. Radenkovic, M. Dugic, I. Radojevic

The answers on the current status and future development of Quantum Science and Technology are presented.

Iman Reihanian, Yunfei Hou, Yu Chen et al.

This paper surveys the use of Generative AI tools, such as ChatGPT and Claude, in computer science education, focusing on key aspects of accuracy, authenticity, and assessment. Through a literature review, we highlight both the challenges and opportunities these AI tools present. While Generative AI improves efficiency and supports creative student work, it raises concerns such as AI hallucinations, error propagation, bias, and blurred lines between AI-assisted and student-authored content. Human oversight is crucial for addressing these concerns. Existing literature recommends adopting hybrid assessment models that combine AI with human evaluation, developing bias detection frameworks, and promoting AI literacy for both students and educators. Our findings suggest that the successful integration of AI requires a balanced approach, considering ethical, pedagogical, and technical factors. Future research may explore enhancing AI accuracy, preserving academic integrity, and developing adaptive models that balance creativity with precision.

Michela Donatelli

Faisal Hamman, Sanghamitra Dutta

This paper introduces a novel information-theoretic perspective on the relationship between prominent group fairness notions in machine learning, namely statistical parity, equalized odds, and predictive parity. It is well known that simultaneous satisfiability of these three fairness notions is usually impossible, motivating practitioners to resort to approximate fairness solutions rather than stringent satisfiability of these definitions. However, a comprehensive analysis of their interrelations, particularly when they are not exactly satisfied, remains largely unexplored. Our main contribution lies in elucidating an exact relationship between these three measures of (un)fairness by leveraging a body of work in information theory called partial information decomposition (PID). In this work, we leverage PID to identify the granular regions where these three measures of (un)fairness overlap and where they disagree with each other leading to potential tradeoffs. We also include numerical simulations to complement our results.

Katell Hernandez Morin, Franck Barbin

The OPTIMICE project, which stands for optimising machine translation of metadata and its integration into the editorial chain, aims at devising a method – transferrable to other journals and disciplinary fields – that combines neural machine translation (DeepL) and human post-editing to improve the quality of article metadata (abstracts, keywords, etc.) from French to English in the editorial process of journals. A team of translation researchers who are also translators worked on four journals edited by the Presses universitaires de Rennes (PUR), in collaboration with the editorial comittees and the MSHB (Maison des sciences de l’Homme en Bretagne). The translation of the paper metadata by their authors and by machine translation was comparatively assessed. A survey on translation practices among researchers in HSS was led, and recommendations for writing and translating metadata were formulated for the organized integration of the methodology within the editorial process.

Sahar Bonyadi, Nadjla Hariri, Seyed Mahdi Taheri et al.

All organizations use data to execute their processes. Organizational data is either generated by the organization itself or created and provided by other organizations. Data and information play an essential role in the decisions and functions of organizational processes. For this reason, data is part of the organization's resources and perhaps the most important source of organizations. The purpose of this study was to provide a data quality model for data governance. The research method was used in a meta-combination. Therefore, out of 268 sources found, during the meta-combination process, 62 articles were used using keywords such as; data, data management, data governance and data quality management were selected in IRANDOC, Science Direct, Google Scholar, Springer, IEEE and ACM databases between 1995-2022. In this study, first a code was considered for all factors extracted from previous studies and then, considering the concept of each code, they were classified in a similar concept. In this way, the concepts of research were identified. Two coders were used to control the extracted codes and categories, and the desired index in this field is the Kappa index. Based on the analysis performed using the content analysis method, a total of 12 main categories (data attribute, data, data fable, data value, initial data value, data pattern, data set, data access, data composition, data formatting, metadata and data objectivity) and 47 sub-categories for data quality management for data governance were identified.

Adam Gronowski, William Paul, Fady Alajaji et al.

Designing machine learning algorithms that are accurate yet fair, not discriminating based on any sensitive attribute, is of paramount importance for society to accept AI for critical applications. In this article, we propose a novel fair representation learning method termed the Rényi Fair Information Bottleneck Method (RFIB) which incorporates constraints for utility, fairness, and compactness (compression) of representation, and apply it to image and tabular data classification. A key attribute of our approach is that we consider - in contrast to most prior work - both demographic parity and equalized odds as fairness constraints, allowing for a more nuanced satisfaction of both criteria. Leveraging a variational approach, we show that our objectives yield a loss function involving classical Information Bottleneck (IB) measures and establish an upper bound in terms of two Rényi measures of order $α$ on the mutual information IB term measuring compactness between the input and its encoded embedding. We study the influence of the $α$ parameter as well as two other tunable IB parameters on achieving utility/fairness trade-off goals, and show that the $α$ parameter gives an additional degree of freedom that can be used to control the compactness of the representation. Experimenting on three different image datasets (EyePACS, CelebA, and FairFace) and two tabular datasets (Adult and COMPAS), using both binary and categorical sensitive attributes, we show that on various utility, fairness, and compound utility/fairness metrics RFIB outperforms current state-of-the-art approaches.

Michael D. Ekstrand, Anubrata Das, Robin Burke et al.

Recommendation, information retrieval, and other information access systems pose unique challenges for investigating and applying the fairness and non-discrimination concepts that have been developed for studying other machine learning systems. While fair information access shares many commonalities with fair classification, the multistakeholder nature of information access applications, the rank-based problem setting, the centrality of personalization in many cases, and the role of user response complicate the problem of identifying precisely what types and operationalizations of fairness may be relevant, let alone measuring or promoting them. In this monograph, we present a taxonomy of the various dimensions of fair information access and survey the literature to date on this new and rapidly-growing topic. We preface this with brief introductions to information access and algorithmic fairness, to facilitate use of this work by scholars with experience in one (or neither) of these fields who wish to learn about their intersection. We conclude with several open problems in fair information access, along with some suggestions for how to approach research in this space.

Ana Cecilia González-Franco, Loreto Robles-Hernández

Los actinomicetos son un reservorio enorme de antibióticos y metabolitos bioactivos y muchos de ellos son excelentes agentes de biocontrol para proteger a las plantas contra fitopatógenos. Aunque miles de antibióticos y metabolitos bioactivos han sido descritos, se cree que estos representan solo una fracción de los compuestos bioactivos producidos por los actinomicetos. En esta revisión se abordan las características generales y propiedades de los actinomicetos como agentes de control biológico, sus mecanismos a través de los cuales realizan el biocontrol y el impacto de la composición química de la pared celular de los hongos fitopatógenos en el proceso de control. Abstract Actinomycetes are an enormous reservoir for antibiotics and bioactive metabolites, and many are excellent biocontrol agents for use in protecting plants against phytopathogens. Although thousands of antibiotics and bioactive metabolites have been described, these are thought to represent only a small fraction of the bioactive compounds produced by actinomycetes. In this review, we summarize the general characteristics and properties of actinomycetes as biocontrol agents, the mechanisms through which the biocontrol occurs, as well as the impact of the phytopathogenic fungal cell wall composition in the control process. Keywords: Streptomyces, competition, parasitism, antibiosis.

Ilka Maria Soares Campos, Rayan Aramís de Brito Feitoza, Henry Pôncio Cruz de Oliveira

Os estudos na área da Ciência da Informação são norteados ao longo dos tempos sob viés que perpassam diferentes campos e correntes teóricas a partir de conceitos diversos. O objetivo deste trabalho é analisar a relação temática das teses de doutorado do Programa de Pós-Graduação de Ciência da Informação da Universidade Federal da Paraíba (2015 a 2019) com as teorias e tendências contemporâneas na Ciência da Informação. A partir de um estudo de caso, realiza uma pesquisa documental, exploratória e descritiva com abordagem qualitativa e quantitativa. Os resultados foram analisados sob a perspectiva da análise de conteúdo por meio da técnica de análise temática. Aponta que as teorias ou tendências de pesquisas em Memória, Regimes de Informação, Cultura Organizacional, Análise do domínio e Aproximações com Arquivologia, Biblioteconomia e Museologia predominam nas teses que compõem o corpus documental. Conclui que os trabalhos de doutorado do Programa de Pós-Graduação em Ciência da Informação analisado foram desenvolvidos com características de acordo com as teorias ou tendências contemporâneas na Ciência da Informação identificadas por Carlos Alberto Ávila de Araújo.

Wahyu Eka Nurhandini

Dinas Perpustakaan Umum dan Arsip Daerah Kota Malang merupakan salah satu perpustakaan umum yang memiliki ruang baca anak. Dengan motto “layanan sepenuh hati”, ruang baca anak memberikan layanan khususnya untuk kunjungan berkelompok. Metode penelitian menggunakan deskriptif kualitatif. Teknik pengumpulan data yang digunakan yaitu wawancara, observasi, dan studi dokumen. Hasil penelitian menunjukan bahwa dengan adanya inovasi layanan, ruang baca anak dapat mengoptimalkan layanan yang diberikan pada kunjungan berkelompok. Selain itu, statistik jumlah kunjungan juga meningkat. Kata kunci: ruang baca anak, inovasi layanan, kunjungan berkelompok Public Library and Regional Archives Service of Malang City is one of the public libraries that has children's reading rooms. With the motto "wholehearted service", children's reading rooms provide services especially for group visits. The research method uses descriptive qualitative.Data collection techniques used in this study were interviews, observation, and study of documents. The results showed that with the innovation of services, children's reading rooms can optimize the services provided, especially for group visits. In addition, statistics on the number of visits also increased. Keywords: children's reading room, service innovation, group visits

Comitê Editorial AtoZ

Informações sobre a elaboração do v.9, n.1 de 2020.

Silvia Cobo-Serrano, Rosario Arquero-Avilés, Gonzalo Marco-Cuenca

Special libraries are essential information and documentation centres for university teachers and researchers due to the quality and richness of their collections. In Spain, it is estimated that there are 2456 special libraries, although many are unknown either generally or among information professionals. These include museum libraries, which are important centres with valuable collections of bibliographic heritage for the area of Humanities and Social Sciences. The aim of this research is to gain an understanding of the real state of these information units and promote the social value of museum libraries in Spain. To do this, a survey was sent to the libraries of state-owned and -managed museums under the General Directorate of Fine Arts and Cultural Property (Ministry of Culture and Sports) of the Government of Spain. This general objective will be accompanied by a review of the scientific literature on various aspects of museum libraries at national and international level. After addressing the research methodology, the results obtained will be discussed and will include the following topics: collection management, library services and staff, economic and technological resources and finally, library management. Conclusions include recommendations for museum librarians and reveal that institutional cooperation is a strategic issue to improve both museum libraries visibility and their social recognition as cultural and research centre.

Zakirova Svitlana, Zakirov Мarat

The article analyzes various scientific approaches to infotainment as a phenomenon of media culture, considers the features of infotainment as a specific type of communication technology. The authors note that infotainment has special methods, techniques, and methods for delivering informative material. Analysis of studies shows that today there is no single view on the essence of infotainment as a phenomenon in the field of mass media and communication. Infotainment arose in the twentieth century as a way to presenting news and facts in an entertaining and humorous way, rather than providing real information. It was aimed at keeping the viewer’s attention as much as possible through strengthening the emotional component and the entertaining nature of the presentation of the material. An important task of infotainment in the last century was to increase the ratings of television channels due to the transformation of both the form and content of the information message. Over time, certain changes have taken place in the meaning of this definition. Infotainment today has certain methods, techniques, methods and means of organizing various types of human and social activities in the field of communication. From the very beginning of its emergence, infotainment was aimed at maintaining the attention of the recipient and through television communication to exert a certain effect on the mass consciousness. Infotainment has in its arsenal a whole range of specific techniques, thanks to which it allows to predict a certain communication performance. Infotainment as a technology is actively and rapidly developing, it has certain specific characteristics and functions that allow it to be interpreted as a broad phenomenon in the synergetic space of information and entertainment. As a phenomenon of media culture, infotainment has a significant impact on various fields of activity and social practices. The consequence of the spread of infotainment technology is such communication technologies as politainment, biznestainment, edutainment, tehnotainment.

Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre et al.

This paper describes a machine learning and data science pipeline for structured information extraction from documents, implemented as a suite of open-source tools and extensions to existing tools. It centers around a methodology for extracting procedural information in the form of recipes, stepwise procedures for creating an artifact (in this case synthesizing a nanomaterial), from published scientific literature. From our overall goal of producing recipes from free text, we derive the technical objectives of a system consisting of pipeline stages: document acquisition and filtering, payload extraction, recipe step extraction as a relationship extraction task, recipe assembly, and presentation through an information retrieval interface with question answering (QA) functionality. This system meets computational information and knowledge management (CIKM) requirements of metadata-driven payload extraction, named entity extraction, and relationship extraction from text. Functional contributions described in this paper include semi-supervised machine learning methods for PDF filtering and payload extraction tasks, followed by structured extraction and data transformation tasks beginning with section extraction, recipe steps as information tuples, and finally assembled recipes. Measurable objective criteria for extraction quality include precision and recall of recipe steps, ordering constraints, and QA accuracy, precision, and recall. Results, key novel contributions, and significant open problems derived from this work center around the attribution of these holistic quality measures to specific machine learning and inference stages of the pipeline, each with their performance measures. The desired recipes contain identified preconditions, material inputs, and operations, and constitute the overall output generated by our computational information and knowledge management (CIKM) system.

Heidrun Wiesenmüller

Verweisseite für den Bericht über die Fortbildungsveranstaltung „Zu Klios Diensten. Fachinformationsdienste und andere Services für die Geschichtswissenschaft“ der Kommission für Fachreferatsarbeit in der Rubrik "Tagungsberichte".

Vuong M. Ngo, Tru H. Cao

Named entities (NE) are objects that are referred to by names such as people, organizations and locations. Named entities and keywords are important to the meaning of a document. We propose a generalized vector space model that combines named entities and keywords. In the model, we take into account different ontological features of named entities, namely, aliases, classes and identifiers. Moreover, we use entity classes to represent the latent information of interrogative words in Wh-queries, which are ignored in traditional keyword-based searching. We have implemented and tested the proposed model on a TREC dataset, as presented and discussed in the paper.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Multiple players are each given one independent sample, about which they can only provide limited information to a central referee. Each player is allowed to describe its observed sample to the referee using a channel from a family of channels $\mathcal{W}$, which can be instantiated to capture both the communication- and privacy-constrained settings and beyond. The referee uses the messages from players to solve an inference problem for the unknown distribution that generated the samples. We derive lower bounds for sample complexity of learning and testing discrete distributions in this information-constrained setting. Underlying our bounds is a characterization of the contraction in chi-square distances between the observed distributions of the samples when information constraints are placed. This contraction is captured in a local neighborhood in terms of chi-square and decoupled chi-square fluctuations of a given channel, two quantities we introduce. The former captures the average distance between distributions of channel output for two product distributions on the input, and the latter for a product distribution and a mixture of product distribution on the input. Our bounds are tight for both public- and private-coin protocols. Interestingly, the sample complexity of testing is order-wise higher when restricted to private-coin protocols.

Stephen G. Kobourov, Giuseppe Liotta, Fabrizio Montecchiani

The notion of 1-planarity is among the most natural and most studied generalizations of graph planarity. A graph is 1-planar if it has an embedding where each edge is crossed by at most another edge. The study of 1-planar graphs dates back to more than fifty years ago and, recently, it has driven increasing attention in the areas of graph theory, graph algorithms, graph drawing, and computational geometry. This annotated bibliography aims to provide a guiding reference to researchers who want to have an overview of the large body of literature about 1-planar graphs. It reviews the current literature covering various research streams about 1-planarity, such as characterization and recognition, combinatorial properties, and geometric representations. As an additional contribution, we offer a list of open problems on 1-planar graphs.

Kiran Garimella, Aristides Gionis, Nikos Parotsidis et al.

Social media has brought a revolution on how people are consuming news. Beyond the undoubtedly large number of advantages brought by social-media platforms, a point of criticism has been the creation of echo chambers and filter bubbles, caused by social homophily and algorithmic personalization. In this paper we address the problem of balancing the information exposure in a social network. We assume that two opposing campaigns (or viewpoints) are present in the network, and that network nodes have different preferences towards these campaigns. Our goal is to find two sets of nodes to employ in the respective campaigns, so that the overall information exposure for the two campaigns is balanced. We formally define the problem, characterize its hardness, develop approximation algorithms, and present experimental evaluation results. Our model is inspired by the literature on influence maximization, but we offer significant novelties. First, balance of information exposure is modeled by a symmetric difference function, which is neither monotone nor submodular, and thus, not amenable to existing approaches. Second, while previous papers consider a setting with selfish agents and provide bounds on best response strategies (i.e., move of the last player), we consider a setting with a centralized agent and provide bounds for a global objective function.