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  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.45
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Breuer, T.; Tavakolpoursaleh, N.; Schaer, P.; Hienert, D.; Schaible, J.; Castro, L.J.: Online Information Retrieval Evaluation using the STELLA Framework (2022) 0.03
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    Abstract
    Involving users in early phases of software development has become a common strategy as it enables developers to consider user needs from the beginning. Once a system is in production, new opportunities to observe, evaluate and learn from users emerge as more information becomes available. Gathering information from users to continuously evaluate their behavior is a common practice for commercial software, while the Cranfield paradigm remains the preferred option for Information Retrieval (IR) and recommendation systems in the academic world. Here we introduce the Infrastructures for Living Labs STELLA project which aims to create an evaluation infrastructure allowing experimental systems to run along production web-based academic search systems with real users. STELLA combines user interactions and log files analyses to enable large-scale A/B experiments for academic search.
  3. Panzer, M.: Dewey Web services : overview (2009) 0.00
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  4. Bauckhage, C.: Moderne Textanalyse : neues Wissen für intelligente Lösungen (2016) 0.00
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    Abstract
    Im Zuge der immer größeren Verfügbarkeit von Daten (Big Data) und rasanter Fortschritte im Daten-basierten maschinellen Lernen haben wir in den letzten Jahren Durchbrüche in der künstlichen Intelligenz erlebt. Dieser Vortrag beleuchtet diese Entwicklungen insbesondere im Hinblick auf die automatische Analyse von Textdaten. Anhand einfacher Beispiele illustrieren wir, wie moderne Textanalyse abläuft und zeigen wiederum anhand von Beispielen, welche praktischen Anwendungsmöglichkeiten sich heutzutage in Branchen wie dem Verlagswesen, der Finanzindustrie oder dem Consulting ergeben.
  5. Williamson, N.J.: Online Klassifikation : Gegenwart und Zukunft (1988) 0.00
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    Theme
    Klassifikationssysteme im Online-Retrieval
  6. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.00
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  7. Schöneberg, U.; Gödert, W.: Erschließung mathematischer Publikationen mittels linguistischer Verfahren (2012) 0.00
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    Abstract
    Die Zahl der mathematik-relevanten Publikationn steigt von Jahr zu Jahr an. Referatedienste wie da Zentralblatt MATH und Mathematical Reviews erfassen die bibliographischen Daten, erschließen die Arbeiten inhaltlich und machen sie - heute über Datenbanken, früher in gedruckter Form - für den Nutzer suchbar. Keywords sind ein wesentlicher Bestandteil der inhaltlichen Erschließung der Publikationen. Keywords sind meist keine einzelnen Wörter, sondern Mehrwortphrasen. Das legt die Anwendung linguistischer Methoden und Verfahren nahe. Die an der FH Köln entwickelte Software 'Lingo' wurde für die speziellen Anforderungen mathematischer Texte angepasst und sowohl zum Aufbau eines kontrollierten Vokabulars als auch zur Extraction von Keywords aus mathematischen Publikationen genutzt. Es ist geplant, über eine Verknüpfung von kontrolliertem Vokabular und der Mathematical Subject Classification Methoden für die automatische Klassifikation für den Referatedienst Zentralblatt MATH zu entwickeln und zu erproben.
  8. Lange, C.; Ion, P.; Dimou, A.; Bratsas, C.; Sperber, W.; Kohlhasel, M.; Antoniou, I.: Getting mathematics towards the Web of Data : the case of the Mathematics Subject Classification (2012) 0.00
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    Abstract
    The Mathematics Subject Classification (MSC), maintained by the American Mathematical Society's Mathematical Reviews (MR) and FIZ Karlsruhe's Zentralblatt für Mathematik (Zbl), is a scheme for classifying publications in mathematics according to their subjects. While it is widely used, its traditional, idiosyncratic conceptualization and representation requires custom implementations of search, query and annotation support. This did not encourage people to create and explore connections of mathematics to subjects of related domains (e.g. science), and it made the scheme hard to maintain. We have reimplemented the current version of MSC2010 as a Linked Open Dataset using SKOS and our focus is concentrated on turning it into the new MSC authority. This paper explains the motivation, and details of our design considerations and how we realized them in the implementation. We present in-the-field use cases and point out how e-science applications can take advantage of the MSC LOD set. We conclude with a roadmap for bootstrapping the presence of mathematical and mathematics-based science, technology, and engineering knowledge on the Web of Data, where it has been noticeably underrepresented so far, starting from MSC/SKOS as a seed.
    Footnote
    Vgl. auch den publizierten Beitrag u.d.T.: Bringing mathematics towards the Web of Data: the case of the Mathematics Subject Classification
  9. Zhai, X.: ChatGPT user experience: : implications for education (2022) 0.00
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    Abstract
    ChatGPT, a general-purpose conversation chatbot released on November 30, 2022, by OpenAI, is expected to impact every aspect of society. However, the potential impacts of this NLP tool on education remain unknown. Such impact can be enormous as the capacity of ChatGPT may drive changes to educational learning goals, learning activities, and assessment and evaluation practices. This study was conducted by piloting ChatGPT to write an academic paper, titled Artificial Intelligence for Education (see Appendix A). The piloting result suggests that ChatGPT is able to help researchers write a paper that is coherent, (partially) accurate, informative, and systematic. The writing is extremely efficient (2-3 hours) and involves very limited professional knowledge from the author. Drawing upon the user experience, I reflect on the potential impacts of ChatGPT, as well as similar AI tools, on education. The paper concludes by suggesting adjusting learning goals-students should be able to use AI tools to conduct subject-domain tasks and education should focus on improving students' creativity and critical thinking rather than general skills. To accomplish the learning goals, researchers should design AI-involved learning tasks to engage students in solving real-world problems. ChatGPT also raises concerns that students may outsource assessment tasks. This paper concludes that new formats of assessments are needed to focus on creativity and critical thinking that AI cannot substitute.
  10. Walker, S.: ¬Der Mensch-Maschine-Dialog bei Online-Benutzer-Katalogen (1987) 0.00
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  11. Bates, M.J.: Designing online catalog subject acces to meet user needs (1989) 0.00
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  12. Butcher, J.E.; Trotter, R.: Building on PRECIS : strategies for online subject access in the British Library (1989) 0.00
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  13. Isaac, A.; Raemy, J.A.; Meijers, E.; Valk, S. De; Freire, N.: Metadata aggregation via linked data : results of the Europeana Common Culture project (2020) 0.00
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    Abstract
    Digital cultural heritage resources are widely available on the web through the digital libraries of heritage institutions. To address the difficulties of discoverability in cultural heritage, the common practice is metadata aggregation, where centralized efforts like Europeana facilitate discoverability by collecting the resources' metadata. We present the results of the linked data aggregation task conducted within the Europeana Common Culture project, which attempted an innovative approach to aggregation based on linked data made available by cultural heritage institutions. This task ran for one year with participation of eleven organizations, involving the three member roles of the Europeana network: data providers, intermediary aggregators, and the central aggregation hub, Europeana. We report on the challenges that were faced by data providers, the standards and specifications applied, and the resulting aggregated metadata.
  14. Wätjen, H.-J.: Mensch oder Maschine? : Auswahl und Erschließung vonm Informationsressourcen im Internet (1996) 0.00
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    Date
    2. 2.1996 15:40:22
  15. Peponakis, M.; Mastora, A.; Kapidakis, S.; Doerr, M.: Expressiveness and machine processability of Knowledge Organization Systems (KOS) : an analysis of concepts and relations (2020) 0.00
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    Abstract
    This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.
  16. Witt, M.: Survey on the use of the catalogue at the médiathèque of the cité des sciences et de l'industrie (CSI) (1993) 0.00
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    Abstract
    An exploratory research study on OPACs was done within the framework of the French PARINFO program by four different teams: ENSSIB-CERSI, City Univ. of London, Médiathèque of the Cité des Sciences et de l'industrie and a firm GSI-ERLI. During the month of June 1992, 650 individual searches on four terminals were collected. The sessions were automatically recorded, accompanied by two online questionnaires, a pre-search and a post-search questionnaire. Some questions were asked orally by an interviewer and the answers noted. The article analyses the researches perceived by user as difficult or impossible. Some examples of the difficulties are given
  17. Robertson, S.E.: OKAPI at TREC-3 (1995) 0.00
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    Abstract
    Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework
  18. Luo, L.; Ju, J.; Li, Y.-F.; Haffari, G.; Xiong, B.; Pan, S.: ChatRule: mining logical rules with large language models for knowledge graph reasoning (2023) 0.00
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    Date
    23.11.2023 19:07:22
  19. Slavic, A.: Interface to classification : some objectives and options (2006) 0.00
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    Theme
    Klassifikationssysteme im Online-Retrieval