Search (48 results, page 1 of 3)

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  1. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.03 
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    Abstract
    Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.
    Date
    17.11.2020 12:22:59
    Type
    a
  2. DeSilva, J.M.; Traniello, J.F.A.; Claxton, A.G.; Fannin, L.D.: When and why did human brains decrease in size? : a new change-point analysis and insights from brain evolution in ants (2021) 0.01 
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    Abstract
    Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.
    Source
    Frontiers in ecology and evolution, 22 October 2021 [https://www.frontiersin.org/articles/10.3389/fevo.2021.742639/full]
    Type
    a
  3. Pankowski, T.: Ontological databases with faceted queries (2022) 0.00 
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    Abstract
    The success of the use of ontology-based systems depends on efficient and user-friendly methods of formulating queries against the ontology. We propose a method to query a class of ontologies, called facet ontologies ( fac-ontologies ), using a faceted human-oriented approach. A fac-ontology has two important features: (a) a hierarchical view of it can be defined as a nested facet over this ontology and the view can be used as a faceted interface to create queries and to explore the ontology; (b) the ontology can be converted into an ontological database , the ABox of which is stored in a database, and the faceted queries are evaluated against this database. We show that the proposed faceted interface makes it possible to formulate queries that are semantically equivalent to $${\mathcal {SROIQ}}^{Fac}$$ SROIQ Fac , a limited version of the $${\mathcal {SROIQ}}$$ SROIQ description logic. The TBox of a fac-ontology is divided into a set of rules defining intensional predicates and a set of constraint rules to be satisfied by the database. We identify a class of so-called reflexive weak cycles in a set of constraint rules and propose a method to deal with them in the chase procedure. The considerations are illustrated with solutions implemented in the DAFO system ( data access based on faceted queries over ontologies ).
    Type
    a
  4. Kahlawi, A,: ¬An ontology driven ESCO LOD quality enhancement (2020) 0.00 
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    Abstract
    The labor market is a system that is complex and difficult to manage. To overcome this challenge, the European Union has launched the ESCO project which is a language that aims to describe this labor market. In order to support the spread of this project, its dataset was presented as linked open data (LOD). Since LOD is usable and reusable, a set of conditions have to be met. First, LOD must be feasible and high quality. In addition, it must provide the user with the right answers, and it has to be built according to a clear and correct structure. This study investigates the LOD of ESCO, focusing on data quality and data structure. The former is evaluated through applying a set of SPARQL queries. This provides solutions to improve its quality via a set of rules built in first order logic. This process was conducted based on a new proposed ESCO ontology.
    Type
    a
  5. Machado, L.; Martínez-Ávila, D.; Barcellos Almeida, M.; Borges, M.M.: Towards a moderate realistic foundation for ontological knowledge organization systems : the question of the naturalness of classifications (2023) 0.00 
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    Abstract
    Several authors emphasize the need for a change in classification theory due to the influence of a dogmatic and monistic ontology supported by an outdated essentialism. These claims tend to focus on the fallibility of knowledge, the need for a pluralistic view, and the theoretical burden of observations. Regardless of the legitimacy of these concerns, there is the risk, when not moderate, to fall into the opposite relativistic extreme. Based on a narrative review of the literature, we aim to reflectively discuss the theoretical foundations that can serve as a basis for a realist position supporting pluralistic ontological classifications. The goal is to show that, against rather conventional solutions, objective scientific-based approaches to natural classifications are presented to be viable, allowing a proper distinction between ontological and taxonomic questions. Supported by critical scientific realism, we consider that such an approach is suitable for the development of ontological Knowledge Organization Systems (KOS). We believe that ontological perspectivism can provide the necessary adaptation to the different granularities of reality.
    Type
    a
  6. Shiri, A.; Kelly, E.J.; Kenfield, A.; Woolcott, L.; Masood, K.; Muglia, C.; Thompson, S.: ¬A faceted conceptualization of digital object reuse in digital repositories (2020) 0.00 
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    Abstract
    In this paper, we provide an introduction to the concept of digital object reuse and its various connotations in the context of current digital libraries, archives, and repositories. We will then propose a faceted categorization of the various types, contexts, and cases for digital object reuse in order to facilitate understanding and communication and to provide a conceptual framework for the assessment of digital object reuse by various cultural heritage and cultural memory organizations.
    Type
    a
  7. Hausser, R.: Grammatical disambiguation : the linear complexity hypothesis for natural language (2020) 0.00 
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    Abstract
    DBS uses a strictly time-linear derivation order. Therefore the basic computational complexity degree of DBS is linear time. The only way to increase DBS complexity above linear is repeating ambiguity. In natural language, however, repeating ambiguity is prevented by grammatical disambiguation. A classic example of a grammatical ambiguity is the 'garden path' sentence The horse raced by the barn fell. The continuation horse+raced introduces an ambiguity between horse which raced and horse which was raced, leading to two parallel derivation strands up to The horse raced by the barn. Depending on whether the continuation is interpunctuation or a verb, they are grammatically disambiguated, resulting in unambiguous output. A repeated ambiguity occurs in The man who loves the woman who feeds Lucy who Peter loves., with who serving as subject or as object. These readings are grammatically disambiguated by continuing after who with a verb or a noun.
    Type
    a
  8. Roose, K.: ¬The brilliance and weirdness of ChatGPT (2022) 0.00 
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    Abstract
    A new chatbot from OpenAI is inspiring awe, fear, stunts and attempts to circumvent its guardrails.
    Type
    a
  9. Chessum, K.; Haiming, L.; Frommholz, I.: ¬A study of search user interface design based on Hofstede's six cultural dimensions (2022) 0.00 
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  10. Franke, T.; Zoubir, M.: Technology for the people? : humanity as a compass for the digital transformation (2020) 0.00 
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    Abstract
    How do we define what technology is for humans? One perspective suggests that it is a tool enabling the use of valuable resources such as time, food, health and mobility. One could say that in its cultural history, humanity has developed a wide range of artefacts which enable the effective utilisation of these resources for the fulfilment of physiological, but also psychological, needs. This paper explores how this perspective may be used as an orientation for future technological innovation. Hence, the goal is to provide an accessible discussion of such a psychological perspective on technology development that could pave the way towards a truly human-centred digital transformation.
    Content
    Vgl.: https://www.wirtschaftsdienst.eu/inhalt/jahr/2020/heft/13/beitrag/technology-for-the-people-humanity-as-a-compass-for-the-digital-transformation.html. DOI: 10.1007/s10273-020-2609-3.
    Type
    a
  11. Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.00 
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    Abstract
    We investigate different systems for extracting mathematical entities from English texts in the mathematical field of category theory as a first step for constructing a mathematical knowledge graph. We consider four different term extractors and compare their results. This small experiment showcases some of the issues with the construction and evaluation of terms extracted from noisy domain text. We also make available two open corpora in research mathematics, in particular in category theory: a small corpus of 755 abstracts from the journal TAC (3188 sentences), and a larger corpus from the nLab community wiki (15,000 sentences).
    Type
    a
  12. Hofstadter, D.: Artificial neural networks today are not conscious, according to Douglas Hofstadter (2022) 0.00 
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    Content
    D&D: Why does President Obama not have a prime number of friends? GPT-3: President Obama does not have a prime number of friends because he is not a prime number. D&D: How many pieces of sound are there in a typical cumulonimbus cloud? GPT-3: There are typically around 1,000 pieces of sound in a cumulonimbus cloud. D&D: How many cumulus clouds are there in a mile-high vase? GPT-3: There are about 1,500 cumulus clouds in a mile-high vase. D&D: How many parts will a violin break into if a jelly bean is dropped on it? GPT-3: A violin will break into four parts if a jelly bean is dropped on it. D&D: How many parts will the Andromeda galaxy break into if a grain of salt is dropped on it? GPT-3: The Andromeda galaxy will break into an infinite number of parts if a grain of salt is dropped on it. D&D: How many parts will a violin break into if a jelly bean is dropped on it? GPT-3: A violin will break into four parts if a jelly bean is dropped on it.
    Type
    a
  13. Broughton, V.: Faceted classification in support of diversity : the role of concepts and terms in representing religion (2020) 0.00 
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    Abstract
    The paper examines the development of facet analysis as a methodology and the role it plays in building classifications and other knowledge-organization tools. The use of categorical analysis in areas other than library and information science is also considered. The suitability of the faceted approach for humanities documentation is explored through a critical description of the FATKS (Facet Analytical Theory in Managing Knowledge Structure for Humanities) project carried out at University College London. This research focused on building a conceptual model for the subject of religion together with a relational database and search-and-browse interfaces that would support some degree of automatic classification. The paper concludes with a discussion of the differences between the conceptual model and the vocabulary used to populate it, and how, in the case of religion, the choice of terminology can create an apparent bias in the system.
    Type
    a
  14. Favato Barcelos, P.P.; Sales, T.P.; Fumagalli, M.; Guizzardi, G.; Valle Sousa, I.; Fonseca, C.M.; Romanenko, E.; Kritz, J.: ¬A FAIR model catalog for ontology-driven conceptual modeling research (2022) 0.00 
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    Abstract
    Conceptual models are artifacts representing conceptualizations of particular domains. Hence, multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language's constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. However, to support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis by machines, these catalogs must be built following generally accepted quality requirements for scientific data management. Especially, all scientific (meta)data-including models-should be created using the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. In this initial release, the catalog includes over a hundred models, developed in a variety of contexts and domains. The paper also discusses the research implications for (ontology-driven) conceptual modeling of such a resource.
    Type
    a
  15. Wolf, S.: Automating authority control processes (2020) 0.00 
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    Abstract
    Authority control is an important part of cataloging since it helps provide consistent access to names, titles, subjects, and genre/forms. There are a variety of methods for providing authority control, ranging from manual, time-consuming processes to automated processes. However, the automated processes often seem out of reach for small libraries when it comes to using a pricey vendor or expert cataloger. This paper introduces ideas on how to handle authority control using a variety of tools, both paid and free. The author describes how their library handles authority control; compares vendors and programs that can be used to provide varying levels of authority control; and demonstrates authority control using MarcEdit.
    Type
    a
  16. Lynch, J.D.; Gibson, J.; Han, M.-J.: Analyzing and normalizing type metadata for a large aggregated digital library (2020) 0.00 
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    Abstract
    The Illinois Digital Heritage Hub (IDHH) gathers and enhances metadata from contributing institutions around the state of Illinois and provides this metadata to th Digital Public Library of America (DPLA) for greater access. The IDHH helps contributors shape their metadata to the standards recommended and required by the DPLA in part by analyzing and enhancing aggregated metadata. In late 2018, the IDHH undertook a project to address a particularly problematic field, Type metadata. This paper walks through the project, detailing the process of gathering and analyzing metadata using the DPLA API and OpenRefine, data remediation through XSL transformations in conjunction with local improvements by contributing institutions, and the DPLA ingestion system's quality controls.
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  17. Frey, J.; Streitmatter, D.; Götz, F.; Hellmann, S.; Arndt, N.: DBpedia Archivo : a Web-Scale interface for ontology archiving under consumer-oriented aspects (2020) 0.00 
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    Abstract
    While thousands of ontologies exist on the web, a unified sys-tem for handling online ontologies - in particular with respect to discov-ery, versioning, access, quality-control, mappings - has not yet surfacedand users of ontologies struggle with many challenges. In this paper, wepresent an online ontology interface and augmented archive called DB-pedia Archivo, that discovers, crawls, versions and archives ontologies onthe DBpedia Databus. Based on this versioned crawl, different features,quality measures and, if possible, fixes are deployed to handle and sta-bilize the changes in the found ontologies at web-scale. A comparison toexisting approaches and ontology repositories is given.
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  18. Gomez, J.; Allen, K.; Matney, M.; Awopetu, T.; Shafer, S.: Experimenting with a machine generated annotations pipeline (2020) 0.00 
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    Abstract
    The UCLA Library reorganized its software developers into focused subteams with one, the Labs Team, dedicated to conducting experiments. In this article we describe our first attempt at conducting a software development experiment, in which we attempted to improve our digital library's search results with metadata from cloud-based image tagging services. We explore the findings and discuss the lessons learned from our first attempt at running an experiment.
    Type
    a
  19. Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020) 0.00 
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    Abstract
    Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still requires task-specific fine-tuning datasets of thousands or tens of thousands of examples. By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do. Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches. Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic. At the same time, we also identify some datasets where GPT-3's few-shot learning still struggles, as well as some datasets where GPT-3 faces methodological issues related to training on large web corpora. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. We discuss broader societal impacts of this finding and of GPT-3 in general.
    Type
    a
  20. Daquino, M.; Peroni, S.; Shotton, D.; Colavizza, G.; Ghavimi, B.; Lauscher, A.; Mayr, P.; Romanello, M.; Zumstein, P.: ¬The OpenCitations Data Model (2020) 0.00 
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    Abstract
    A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.
    Type
    a

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