Search (163 results, page 1 of 9)

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Source

https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN

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Content

Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.

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Abstract

Purpose Belkin and Robertson (1976a) reflected on the ethical implications of theoretical research in information science and warned that there was potential for abuse of knowledge gained by undertaking such research and applying it to information systems. In particular, they identified the domains of advertising and political propaganda that posed particular problems. The purpose of this literature review is to revisit these ideas in the light of recent events in global information systems that demonstrate that their fears were justified. Design/methodology/approach The authors revisit the theory in information science that Belkin and Robertson used to build their argument, together with the discussion on ethics that resulted from this work in the late 1970s and early 1980s. The authors then review recent literature in the field of information systems, specifically information retrieval, social media and recommendation systems that highlight the problems identified by Belkin and Robertson. Findings Information science theories have been used in conjunction with empirical evidence gathered from user interactions that have been detrimental to both individuals and society. It is argued in the paper that the information science and systems communities should find ways to return control to the user wherever possible, and the ways to achieve this are considered. Research limitations/implications The ethical issues identified require a multidisciplinary approach with research in information science, computer science, information systems, business, sociology, psychology, journalism, government and politics, etc. required. This is too large a scope to deal with in a literature review, and we focus only on the design and implementation of information systems (Zimmer, 2008a) through an information science and information systems perspective. Practical implications The authors argue that information systems such as search technologies, social media applications and recommendation systems should be designed with the recipient of the information in mind (Paisley and Parker, 1965), not the sender of that information. Social implications Information systems designed ethically and with users in mind will go some way to addressing the ill effects typified by the problems for individuals and society evident in global information systems. Originality/value The authors synthesize the evidence from the literature to provide potential technological solutions to the ethical issues identified, with a set of recommendations to information systems designers and implementers.

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Abstract

Cultural heritage institutions are publishing their digital collections over the web as LOD. This is is a new step in the patrimonialization and curatorial processes developed by such institutions. Many of these collections are thematically superimposed and complementary. Frequently, objects in these collections present culturally relevant relationships, such as a book about a painting, or a draft or sketch of a famous painting, etc. LOD technology enables such heritage records to be interlinked, achieving interoperability and adding value to digital collections, thus empowering heritage institutions. An aim of this research is characterizing such culturally relevant relationships and organizing them in a vocabulary. Use cases or examples of relationships between objects suggested by curators or mentioned in literature and in the conceptual models as FRBR/LRM, CIDOC CRM and RiC-CM, were collected and used as examples or inspiration of cultural relevant relationships. Relationships identified are collated and compared for identifying those with the same or similar meaning, synthesized and normalized. A set of thirty-three culturally relevant relationships are identified and formalized as a LOD property vocabulary to be used by digital curators to interlink digital collections. The results presented are provisional and a starting point to be discussed, tested, and enhanced.

Date

4. 3.2020 14:22:41

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Abstract

Purpose Personal information management (PIM) is an activity in which people store information items in order to retrieve them later. The purpose of this paper is to test and quantify the effect of factors related to collection size, file properties and workload on file retrieval success and efficiency. Design/methodology/approach In the study, 289 participants retrieved 1,557 of their shared files in a naturalistic setting. The study used specially developed software designed to collect shared files' names and present them as targets for the retrieval task. The dependent variables were retrieval success, retrieval time and misstep/s. Findings Various factors compromise shared files retrieval including: collection size (large number of files), file properties (multiple versions, size of team sharing the file, time since most recent retrieval and folder depth) and workload (daily e-mails sent and received). The authors discuss theoretical reasons for these negative effects and suggest possible ways to overcome them. Originality/value Retrieval is the main reason people manage personal information. It is essential for retrieval to be successful and efficient, as information cannot be used unless it can be re-accessed. Prior PIM research has assumed that factors related to collection size, file properties and workload affect file retrieval. However, this is the first study to systematically quantify the negative effects of these factors. As each of these factors is expected to be exacerbated in the future, this study is a necessary first step toward addressing these problems.

Date

20. 1.2015 18:30:22

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Abstract

Knowledge-enhanced short-text matching has been a significant task attracting much attention in recent years. However, the existing approaches cannot effectively balance effect and efficiency. Effective models usually consist of complex network structures leading to slow inference speed and the difficulties of applications in actual practice. In addition, most knowledge-enhanced models try to link the mentions in the text to the entities of the knowledge graphs-the difficulties of entity linking decrease the generalizability among different datasets. To address these problems, we propose a lightweight Semantic-Enhanced Interactive Network (SEIN) model for efficient short-text matching. Unlike most current research, SEIN employs an unsupervised method to select WordNet's most appropriate paraphrase description as the external semantic knowledge. It focuses on integrating semantic information and interactive information of text while simplifying the structure of other modules. We conduct intensive experiments on four real-world datasets, that is, Quora, Twitter-URL, SciTail, and SICK-E. Compared with state-of-the-art methods, SEIN achieves the best performance on most datasets. The experimental results proved that introducing external knowledge could effectively improve the performance of the short-text matching models. The research sheds light on the role of lightweight models in leveraging external knowledge to improve the effect of short-text matching.

Date

22. 1.2023 19:05:27

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Abstract

This article presents approaches used to solve the problem of selecting AI technologies and tools to obtain the creativity fostering functionalities of an innovative knowledge platform. The aforementioned selection problem has been lagging behind other software-specific aspects of online knowledge platform and learning platform development so far. We linked technological recommendations from group decision support exercises to the platform design aims and constraints using an expert Delphi survey and multicriteria analysis methods. The links between expected advantages of using selected AI building tools, AI-related system functionalities, and their ongoing relevance until 2030 were assessed and used to optimize the learning scenarios and in planning the future development of the platform. The selected technologies allowed the platform management to implement the desired functionalities, thus harnessing the potential of open innovation platforms more effectively and delivering a model for the development of a relevant class of advanced open-access knowledge provision systems. Additionally, our approach is an essential part of digital sustainability and AI-alignment strategy for the aforementioned class of systems. The knowledge platform, which serves as a case study for our methodology has been developed within an EU Horizon 2020 research project.

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Abstract

Personalization of information retrieval (PIR) is aimed at tailoring a search toward individual users and user groups by taking account of additional information about users besides their queries. In the past two decades or so, PIR has received extensive attention in both academia and industry. This article surveys the literature of personalization in text retrieval, following a framework for aspects or factors that can be used for personalization. The framework consists of additional information about users that can be explicitly obtained by asking users for their preferences, or implicitly inferred from users' search behaviors. Users' characteristics and contextual factors such as tasks, time, location, etc., can be helpful for personalization. This article also addresses various issues including when to personalize, the evaluation of PIR, privacy, usability, etc. Based on the extensive review, challenges are discussed and directions for future effort are suggested.

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Content

"Die Englischsprachige Wikipedia verfügt jetzt über mehr als 6 Millionen Artikel. An zweiter Stelle kommt die deutschsprachige Wikipedia mit 2.3 Millionen Artikeln, an dritter Stelle steht die französischsprachige Wikipedia mit 2.1 Millionen Artikeln (via Researchbuzz: Firehose <https://rbfirehose.com/2020/01/24/techcrunch-wikipedia-now-has-more-than-6-million-articles-in-english/> und Techcrunch <https://techcrunch.com/2020/01/23/wikipedia-english-six-million-articles/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Techcrunch+%28TechCrunch%29&guccounter=1&guce_referrer=aHR0cHM6Ly9yYmZpcmVob3NlLmNvbS8yMDIwLzAxLzI0L3RlY2hjcnVuY2gtd2lraXBlZGlhLW5vdy1oYXMtbW9yZS10aGFuLTYtbWlsbGlvbi1hcnRpY2xlcy1pbi1lbmdsaXNoLw&guce_referrer_sig=AQAAAK0zHfjdDZ_spFZBF_z-zDjtL5iWvuKDumFTzm4HvQzkUfE2pLXQzGS6FGB_y-VISdMEsUSvkNsg2U_NWQ4lwWSvOo3jvXo1I3GtgHpP8exukVxYAnn5mJspqX50VHIWFADHhs5AerkRn3hMRtf_R3F1qmEbo8EROZXp328HMC-o>). 250120 via digithek ch = #fineBlog s.a.: Angesichts der Veröffentlichung des 6-millionsten Artikels vergangene Woche in der englischsprachigen Wikipedia hat die Community-Zeitungsseite "Wikipedia Signpost" ein Moratorium bei der Veröffentlichung von Unternehmensartikeln gefordert. Das sei kein Vorwurf gegen die Wikimedia Foundation, aber die derzeitigen Maßnahmen, um die Enzyklopädie gegen missbräuchliches undeklariertes Paid Editing zu schützen, funktionierten ganz klar nicht. *"Da die ehrenamtlichen Autoren derzeit von Werbung in Gestalt von Wikipedia-Artikeln überwältigt werden, und da die WMF nicht in der Lage zu sein scheint, dem irgendetwas entgegenzusetzen, wäre der einzige gangbare Weg für die Autoren, fürs erste die Neuanlage von Artikeln über Unternehmen zu untersagen"*, schreibt der Benutzer Smallbones in seinem Editorial <https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2020-01-27/From_the_editor> zur heutigen Ausgabe."

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Abstract

In 2015, the PCC Task Group on URIs in MARC was tasked to identify and address linked data identifiers deployment in the current MARC format. By way of a pilot test, a survey, MARC Discussion papers, Proposals, etc., the Task Group initiated and introduced changes to MARC encoding. The Task Group succeeded in laying the ground work for preparing library data transition from MARC data to a linked data, RDF environment.

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Abstract

In 2015, the PCC Task Group on URIs in MARC was tasked to identify and address linked data identifiers deployment in the current MARC format. By way of a pilot test, a survey, MARC Discussion papers, Proposals, etc., the Task Group initiated and introduced changes to MARC encoding. The Task Group succeeded in laying the ground work for preparing library data transition from MARC data to a linked data, RDF environment.

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Abstract

Die Digitalisierung des kulturellen Erbes in Bibliotheken, Archiven und Museen hat in den letzten Jahrzehnten eine rasant zunehmende Verfügbarkeit kultureller Inhalte im Web bewirkt - so hat die Staatsbibliothek zu Berlin - Preußischer Kulturbesitz (SBB-PK) rund 170.000 Werke (Bücher, Zeitschriften, Zeitungen, Karten, Notenschriften etc.) aus ihrem reichhaltigen Bestand digitalisiert und über ein eigenes Online-Portal bereitgestellt (Stand Mai 2020). Noch deutlicher wird die immense Menge der durch die Digitalisierung entstandenen digitalen Kulturobjekte beim Blick auf die von Aggregatoren gebildeten Sammlungen - so beinhaltet die Deutsche Digitale Bibliothek etwa 33 Millionen Nachweise für Digitalisate aus Kultureinrichtungen (Stand Mai 2020), die europäische digitale Bibliothek Europeana weist knapp 60 Millionen digitalisierte Kulturobjekte nach (Stand Mai 2020).

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Abstract

Bei der Informationsrecherche z. B. für einen Vortrag, eine bestimmte Fragestellung oder bei der Einarbeitung in ein neues Aufgabengebiet etc. kann man schnell durch die endlose Informationsflut überfordert sein. Daher braucht es ein methodisches und strukturiertes Vorgehen, um relevante und verlässliche Informationen zu erhalten. Der Informationsrecherchevorgang beinhaltet, zuerst den Informationsbedarf zu erkennen und eine entsprechende Suchstrategie zu entwickeln. Das bedeutet eine sinnvolle Themeneingrenzung, Suchbegriffe festzulegen und auch die Art und Form der Informationen zu bestimmen. Bei der elektronischen Informationsbeschaffung gilt es zunächst, die Sucheingabe zu optimieren, z. B. über eine Stichwort- oder Schlagwortsuche und mit Hilfe der Verwendung von Filtern, Booleschen Operatoren, Trunkierungszeichen und anderen Suchfunktionen. Für die Qualitätssicherung in der Informationsrecherche, vor allem bei der Auswahl, Nutzung und Bewertung von Informationsressourcen, sind Quellenkenntnis, Quellenauswahl und Quellenbewertung zentrale Themen, denen sich dieser Beitrag in der Hauptsache widmet.

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Abstract

Generative Pre-trained Transformer (GPT) models by OpenAI have taken natural language processing (NLP) community by storm by introducing very powerful language models. These models can perform various NLP tasks like question answering, textual entailment, text summarisation etc. without any supervised training. These language models need very few to no examples to understand the tasks and perform equivalent or even better than the state-of-the-art models trained in supervised fashion. In this article we will cover the journey of these models and understand how they have evolved over a period of 2 years. 1. Discussion of GPT-1 paper (Improving Language Understanding by Generative Pre-training). 2. Discussion of GPT-2 paper (Language Models are unsupervised multitask learners) and its subsequent improvements over GPT-1. 3. Discussion of GPT-3 paper (Language models are few shot learners) and the improvements which have made it one of the most powerful models NLP has seen till date. This article assumes familiarity with the basics of NLP terminologies and transformer architecture.

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Abstract

Das erste durch KI verfasste Weisheitsbuch. »Die Künstliche Intelligenz sieht den Menschen, wie er ist. Es gibt für sie keinen Gott, keine Rituale, keinen Himmel, keine Hölle, keine Engel. Es gibt für sie nur empfindsame Wesen.« GPT-3. Dieses Buch enthält Weisheitstexte, die durch die modernste KI im Bereich der Spracherkennung verfasst wurden. Es ist die GPT-3, die durch die Technikerin Jasmine Wang gesteuert wird. Die originären Texte von GPT-3 werden von dem international bekannten Dichter Iain S. Thomas kuratiert. Die Basis von GPT-3 reicht von den Weisheitsbücher der Menschheit bis hin zu modernen Texten. GPT-3 antwortet auf Fragen wie: Was macht den Mensch zum Menschen? Was bedeutet es zu lieben? Wie führen wir ein erfülltes Leben? etc. und ist in der Lage, eigene Sätze zu kreieren. So wird eine zeitgenössische und noch nie dagewesene Erforschung von Sinn und Spiritualität geschaffen, die zu einem neuen Verständnis dessen inspiriert, was uns zu Menschen macht.

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Date

27. 1.2023 16:22:55

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Abstract

In bestimmten Gebieten der Mathematik werden Algorithmen eingesetzt, um zu entscheiden, ob Aussagen wahr oder falsch sind. Dafür müssen wir allerdings sicherstellen, dass diese Handlungsvorschriften zur Lösung eines Problems auch wirklich funktionieren.

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Abstract

Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).

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Abstract

Here, we report on a qualitative study that examined research information management (RIM) ecosystems on research university campuses from the perspectives of research information (RI) managers and librarians. In the study, we identified 21 RIM services offered to researchers, ranging from discovering, storing, and sharing authored content to identifying expertise, recruiting faculty, and ensuring the diversity of committee assignments. In addition, we identified 15 types of RIM service provision and adoption problems, analyzed their activity structures, and connected them to strategies for their resolution. Finally, we report on skills that the study participants reported as being needed in their work. These findings can inform the development of best practice guides for RIM on university campuses. The study also advances the state of the art of RIM research by applying the typology of contradictions from activity theory to categorize the problems of RIM service provision and connect their resolution to theories and findings of prior studies in the literature. In this way, the research expands the theoretical base used to study RIM in general and RIM at research universities in particular.

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Abstract

Research Data Management (RDM) promises to make research outputs more transparent, findable, and reproducible. Strategies to streamline data management across disciplines are of key importance. This paper presents results of an institutional survey (N = 258) at a medium-sized Austrian university with a STEM focus, supplemented with interviews (N = 18), to give an overview of the state-of-play of RDM practices across faculties and disciplinary contexts. RDM services are on the rise but remain somewhat behind leading countries like the Netherlands and UK, showing only the beginnings of a culture attuned to RDM. There is considerable variation between faculties and institutes with respect to data amounts, complexity of data sets, data collection and analysis, and data archiving. Data sharing practices within fields tend to be inconsistent. RDM is predominantly regarded as an administrative task, to the detriment of considerations of good research practice. Problems with RDM fall in two categories: Generic problems transcend specific research interests, infrastructures, and departments while discipline-specific problems need a more targeted approach. The paper extends the state-of-the-art on RDM practices by combining in-depth qualitative material with quantified, detailed data about RDM practices and needs. The findings should be of interest to any comparable research institution with a similar agenda.