Search (279 results, page 1 of 14)

  • × year_i:[2020 TO 2030}
  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.10 
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Gabler, S.: Vergabe von DDC-Sachgruppen mittels eines Schlagwort-Thesaurus (2021) 0.08 
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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.
  3. Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023) 0.05 
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    Abstract
    To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.
    Date
    21. 3.2023 19:22:14
  4. Wu, Z.; Li, R.; Zhou, Z.; Guo, J.; Jiang, J.; Su, X.: ¬A user sensitive subject protection approach for book search service (2020) 0.05 
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    Abstract
    In a digital library, book search is one of the most important information services. However, with the rapid development of network technologies such as cloud computing, the server-side of a digital library is becoming more and more untrusted; thus, how to prevent the disclosure of users' book query privacy is causing people's increasingly extensive concern. In this article, we propose to construct a group of plausible fake queries for each user book query to cover up the sensitive subjects behind users' queries. First, we propose a basic framework for the privacy protection in book search, which requires no change to the book search algorithm running on the server-side, and no compromise to the accuracy of book search. Second, we present a privacy protection model for book search to formulate the constraints that ideal fake queries should satisfy, that is, (i) the feature similarity, which measures the confusion effect of fake queries on users' queries, and (ii) the privacy exposure, which measures the cover-up effect of fake queries on users' sensitive subjects. Third, we discuss the algorithm implementation for the privacy model. Finally, the effectiveness of our approach is demonstrated by theoretical analysis and experimental evaluation.
    Date
    6. 1.2020 17:22:25
  5. ¬Der Student aus dem Computer (2023) 0.05 
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    Date
    27. 1.2023 16:22:55
  6. He, C.; Wu, J.; Zhang, Q.: Proximity-aware research leadership recommendation in research collaboration via deep neural networks (2022) 0.04 
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    Abstract
    Collaborator recommendation is of great significance for facilitating research collaboration. Proximities have been demonstrated to be significant factors and determinants of research collaboration. Research leadership is associated with not only the capability to integrate resources to launch and sustain the research project but also the production and academic impact of the collaboration team. However, existing studies mainly focus on social or cognitive proximity, failing to integrate critical proximities comprehensively. Besides, existing studies focus on recommending relationships among all the coauthors, ignoring leadership in research collaboration. In this article, we propose a proximity-aware research leadership recommendation (PRLR) model to systematically integrate critical node attribute information (critical proximities) and network features to conduct research leadership recommendation by predicting the directed links in the research leadership network. PRLR integrates cognitive, geographical, and institutional proximity as node attribute information and constructs a leadership-aware coauthorship network to preserve the research leadership information. PRLR learns the node attribute information, the local network features, and the global network features with an autoencoder model, a joint probability constraint, and an attribute-aware skip-gram model, respectively. Extensive experiments and ablation studies have been conducted, demonstrating that PRLR significantly outperforms the state-of-the-art collaborator recommendation models in research leadership recommendation.
  7. Tang, X.-B.; Fu, W.-G.; Liu, Y.: Knowledge big graph fusing ontology with property graph : a case study of financial ownership network (2021) 0.04 
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    Abstract
    The scale of knowledge is growing rapidly in the big data environment, and traditional knowledge organization and services have faced the dilemma of semantic inaccuracy and untimeliness. From a knowledge fusion perspective-combining the precise semantic superiority of traditional ontology with the large-scale graph processing power and the predicate attribute expression ability of property graph-this paper presents an ontology and property graph fusion framework (OPGFF). The fusion process is divided into content layer fusion and constraint layer fusion. The result of the fusion, that is, the knowledge representation model is called knowledge big graph. In addition, this paper applies the knowledge big graph model to the ownership network in the China's financial field and builds a financial ownership knowledge big graph. Furthermore, this paper designs and implements six consistency inference algorithms for finding contradictory data and filling in missing data in the financial ownership knowledge big graph, five of which are completely domain agnostic. The correctness and validity of the algorithms have been experimentally verified with actual data. The fusion OPGFF framework and the implementation method of the knowledge big graph could provide technical reference for big data knowledge organization and services.
  8. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.04 
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    Abstract
    Predicting a researcher's knowledge trajectories beyond their current foci can leverage potential inter-/cross-/multi-disciplinary interactions to achieve exploratory innovation. In this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation. The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer. A novel link prediction approach with a diffusion strategy is then used to capture the interactions between social elements (e.g., collaboration) and knowledge elements (e.g., technological similarity) in the process of exploratory innovation. This diffusion strategy differentiates the interactions occurring among homogeneous and heterogeneous nodes in the heterogeneous bibliometric network and weights the strengths of these interactions. Two sets of experiments-one with a local dataset and the other with a global dataset-demonstrate that the proposed method is prior to 10 selected baselines in link prediction, recommender systems, and upstream graph representation learning. A case study recommending knowledge trajectories of information scientists with topical hierarchy and explainable mediators reveals the proposed method's reliability and potential practical uses in broad scenarios.
    Date
    22. 6.2023 18:07:12
  9. Berg, A.; Nelimarkka, M.: Do you see what I see? : measuring the semantic differences in image-recognition services' outputs (2023) 0.04 
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    Abstract
    As scholars increasingly undertake large-scale analysis of visual materials, advanced computational tools show promise for informing that process. One technique in the toolbox is image recognition, made readily accessible via Google Vision AI, Microsoft Azure Computer Vision, and Amazon's Rekognition service. However, concerns about such issues as bias factors and low reliability have led to warnings against research employing it. A systematic study of cross-service label agreement concretized such issues: using eight datasets, spanning professionally produced and user-generated images, the work showed that image-recognition services disagree on the most suitable labels for images. Beyond supporting caveats expressed in prior literature, the report articulates two mitigation strategies, both involving the use of multiple image-recognition services: Highly explorative research could include all the labels, accepting noisier but less restrictive analysis output. Alternatively, scholars may employ word-embedding-based approaches to identify concepts that are similar enough for their purposes, then focus on those labels filtered in.
  10. Haimson, O.L.; Carter, A.J.; Corvite, S.; Wheeler, B.; Wang, L.; Liu, T.; Lige, A.: ¬The major life events taxonomy : social readjustment, social media information sharing, and online network separation during times of life transition (2021) 0.03 
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    Abstract
    When people experience major life changes, this often impacts their self-presentation, networks, and online behavior in substantial ways. To effectively study major life transitions and events, we surveyed a large U.S. sample (n = 554) to create the Major Life Events Taxonomy, a list of 121 life events in 12 categories. We then applied this taxonomy to a second large U.S. survey sample (n = 775) to understand on average how much social readjustment each event required, how likely each event was to be shared on social media with different types of audiences, and how much online network separation each involved. We found that social readjustment is positively correlated with sharing on social media, with both broad audiences and close ties as well as in online spaces separate from one's network of known ties. Some life transitions involve high levels of sharing with both separate audiences and broad audiences on social media, providing evidence for what previous research has called social media as social transition machinery. Researchers can use the Major Life Events Taxonomy to examine how people's life transition experiences relate to their behaviors, technology use, and health and well-being outcomes.
    Date
    10. 6.2021 19:22:47
  11. Yu, C.; Xue, H.; An, L.; Li, G.: ¬A lightweight semantic-enhanced interactive network for efficient short-text matching (2023) 0.03 
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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
  12. Schreur, P.E.: ¬The use of Linked Data and artificial intelligence as key elements in the transformation of technical services (2020) 0.03 
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    Abstract
    Library Technical Services have benefited from numerous stimuli. Although initially looked at with suspicion, transitions such as the move from catalog cards to the MARC formats have proven enormously helpful to libraries and their patrons. Linked data and Artificial Intelligence (AI) hold the same promise. Through the conversion of metadata surrogates (cataloging) to linked open data, libraries can represent their resources on the Semantic Web. But in order to provide some form of controlled access to unstructured data, libraries must reach beyond traditional cataloging to new tools such as AI to provide consistent access to a growing world of full-text resources.
  13. Palsdottir, A.: Data literacy and management of research data : a prerequisite for the sharing of research data (2021) 0.03 
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    Abstract
    Purpose The purpose of this paper is to investigate the knowledge and attitude about research data management, the use of data management methods and the perceived need for support, in relation to participants' field of research. Design/methodology/approach This is a quantitative study. Data were collected by an email survey and sent to 792 academic researchers and doctoral students. Total response rate was 18% (N = 139). The measurement instrument consisted of six sets of questions: about data management plans, the assignment of additional information to research data, about metadata, standard file naming systems, training at data management methods and the storing of research data. Findings The main finding is that knowledge about the procedures of data management is limited, and data management is not a normal practice in the researcher's work. They were, however, in general, of the opinion that the university should take the lead by recommending and offering access to the necessary tools of data management. Taken together, the results indicate that there is an urgent need to increase the researcher's understanding of the importance of data management that is based on professional knowledge and to provide them with resources and training that enables them to make effective and productive use of data management methods. Research limitations/implications The survey was sent to all members of the population but not a sample of it. Because of the response rate, the results cannot be generalized to all researchers at the university. Nevertheless, the findings may provide an important understanding about their research data procedures, in particular what characterizes their knowledge about data management and attitude towards it. Practical implications Awareness of these issues is essential for information specialists at academic libraries, together with other units within the universities, to be able to design infrastructures and develop services that suit the needs of the research community. The findings can be used, to develop data policies and services, based on professional knowledge of best practices and recognized standards that assist the research community at data management. Originality/value The study contributes to the existing literature about research data management by examining the results by participants' field of research. Recognition of the issues is critical in order for information specialists in collaboration with universities to design relevant infrastructures and services for academics and doctoral students that can promote their research data management.
    Date
    20. 1.2015 18:30:22
  14. Singh, V.K.; Chayko, M.; Inamdar, R.; Floegel, D.: Female librarians and male computer programmers? : gender bias in occupational images on digital media platforms (2020) 0.03 
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    Abstract
    Media platforms, technological systems, and search engines act as conduits and gatekeepers for all kinds of information. They often influence, reflect, and reinforce gender stereotypes, including those that represent occupations. This study examines the prevalence of gender stereotypes on digital media platforms and considers how human efforts to create and curate messages directly may impact these stereotypes. While gender stereotyping in social media and algorithms has received some examination in the recent literature, its prevalence in different types of platforms (for example, wiki vs. news vs. social network) and under differing conditions (for example, degrees of human- and machine-led content creation and curation) has yet to be studied. This research explores the extent to which stereotypes of certain strongly gendered professions (librarian, nurse, computer programmer, civil engineer) persist and may vary across digital platforms (Twitter, the New York Times online, Wikipedia, and Shutterstock). The results suggest that gender stereotypes are most likely to be challenged when human beings act directly to create and curate content in digital platforms, and that highly algorithmic approaches for curation showed little inclination towards breaking stereotypes. Implications for the more inclusive design and use of digital media platforms, particularly with regard to mediated occupational messaging, are discussed.
  15. Rieder, B.: Engines of order : a mechanology of algorithmic techniques (2020) 0.03 
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    Abstract
    Software has become a key component of contemporary life and algorithmic techniques that rank, classify, or recommend anything that fits into digital form are everywhere. This book approaches the field of information ordering conceptually as well as historically. Building on the philosophy of Gilbert Simondon and the cultural techniques tradition, it first examines the constructive and cumulative character of software and shows how software-making constantly draws on large reservoirs of existing knowledge and techniques. It then reconstructs the historical trajectories of a series of algorithmic techniques that have indeed become the building blocks for contemporary practices of ordering. Developed in opposition to centuries of library tradition, coordinate indexing, text processing, machine learning, and network algorithms instantiate dynamic, perspectivist, and interested forms of arranging information, ideas, or people. Embedded in technical infrastructures and economic logics, these techniques have become engines of order that transform the spaces they act upon.
    LCSH
    Algorithms ; Computer software
    Subject
    Algorithms ; Computer software
  16. 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) 0.03 
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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.
  17. Hottenrott, H.; Rose, M.E.; Lawson, C.: ¬The rise of multiple institutional affiliations in academia (2021) 0.03 
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    Abstract
    This study provides the first systematic, international, large-scale evidence on the extent and nature of multiple institutional affiliations on journal publications. Studying more than 15 million authors and 22 million articles from 40 countries we document that: In 2019, almost one in three articles was (co-)authored by authors with multiple affiliations and the share of authors with multiple affiliations increased from around 10% to 16% since 1996. The growth of multiple affiliations is prevalent in all fields and it is stronger in high impact journals. About 60% of multiple affiliations are between institutions from within the academic sector. International co-affiliations, which account for about a quarter of multiple affiliations, most often involve institutions from the United States, China, Germany and the United Kingdom, suggesting a core-periphery network. Network analysis also reveals a number communities of countries that are more likely to share affiliations. We discuss potential causes and show that the timing of the rise in multiple affiliations can be linked to the introduction of more competitive funding structures such as "excellence initiatives" in a number of countries. We discuss implications for science and science policy.
  18. Soares-Silva, D.; Salati Marcondes de Moraes, G.H.; Cappellozza, A.; Morini, C.: Explaining library user loyalty through perceived service quality : what is wrong? (2020) 0.03 
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    Abstract
    This study validates the adaptation of a loyalty scale for the library scenario and recovers the hierarchical nature of the perceived service quality (PSQ) by operationalizing it as a second-order level construct, composed by the determinants of service quality (DSQ) identified by Parasuraman, Zeithaml, and Berry in 1985. Our hypothesis was that DSQ are distinct and complementary dimensions, in opposition to the overlapping of DSQ proposed in the SERVQUAL and LibQUAL+® models. In addition, the influence of PSQ on user loyalty (UL) was investigated. Using structural equation modeling, we analyzed the survey data of 1,028 users of a network of academic libraries and report 2 main findings. First, it was shown that the 10 DSQ are statistically significant for the evaluation of PSQ. Second, we demonstrated the positive effect of PSQ for UL. The model presented may be used as a diagnostic and benchmarking tool for managers, coordinators, and librarians who seek to evaluate and/or assess the quality of the services offered by their libraries, as well as to identify and/or manage the loyalty level of their users.
  19. Rieger, F.: Lügende Computer (2023) 0.03 
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    Date
    16. 3.2023 19:22:55
  20. Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021) 0.03 
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    Abstract
    Purpose The purpose of the paper is to analyse the interactions of bridging users in Twitter discussions about vaccination. Design/methodology/approach Conversational threads were collected through filtering the Twitter stream using keywords and the most active participants in the conversations. Following data collection and anonymisation of tweets and user profiles, a retweet network was created to find users bridging the main clusters. Four conversations were selected, ranging from 456 to 1,983 tweets long, and then analysed through content analysis. Findings Although different opinions met in the discussions, a consensus was rarely built. Many sub-threads involved insults and criticism, and participants seemed not interested in shifting their positions. However, examples of reasoned discussions were also found. Originality/value The study analyses conversations on Twitter, which is rarely studied. The focus on the interactions of bridging users adds to the uniqueness of the paper.
    Date
    20. 1.2015 18:30:22

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