Search (32 results, page 1 of 2)

  • × year_i:[2020 TO 2030}
  • × theme_ss:"Wissensrepräsentation"
  1. Soshnikov, D.: ROMEO: an ontology-based multi-agent architecture for online information retrieval (2021) 0.02 
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    Abstract
    This paper describes an approach to path-finding in the intelligent graphs, with vertices being intelligent agents. A possible implementation of this approach is described, based on logical inference in distributed frame hierarchy. Presented approach can be used for implementing distributed intelligent information systems that include automatic navigation and path generation in hypertext, which can be used, for example in distance education, as well as for organizing intelligent web catalogues with flexible ontology-based information retrieval.
  2. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.01 
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    Abstract
    We present an overview of the NTCIR Math Tasks organized during NTCIR-10, 11, and 12. These tasks are primarily dedicated to techniques for searching mathematical content with formula expressions. In this chapter, we first summarize the task design and introduce test collections generated in the tasks. We also describe the features and main challenges of mathematical information retrieval systems and discuss future perspectives in the field.
    Series
    ¬The Information retrieval series, vol 43
    Source
    Evaluating information retrieval and access tasks. Eds.: Sakai, T., Oard, D., Kando, N. [https://doi.org/10.1007/978-981-15-5554-1_12]
  3. Tramullas, J.; Garrido-Picazo, P.; Sánchez-Casabón, A.I.: Use of Wikipedia categories on information retrieval research : a brief review (2020) 0.01 
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    Abstract
    Wikipedia categories, a classification scheme built for organizing and describing Wikpedia articles, are being applied in computer science research. This paper adopts a systematic literature review approach, in order to identify different approaches and uses of Wikipedia categories in information retrieval research. Several types of work are identified, depending on the intrinsic study of the categories structure, or its use as a tool for the processing and analysis of other documentary corpus different to Wikipedia. Information retrieval is identified as one of the major areas of use, in particular its application in the refinement and improvement of search expressions, and the construction of textual corpus. However, the set of available works shows that in many cases research approaches applied and results obtained can be integrated into a comprehensive and inclusive concept of information retrieval.
  4. MacFarlane, A.; Missaoui, S.; Frankowska-Takhari, S.: On machine learning and knowledge organization in multimedia information retrieval (2020) 0.01 
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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).
  5. Baroncini, S.; Sartini, B.; Erp, M. Van; Tomasi, F.; Gangemi, A.: Is dc:subject enough? : A landscape on iconography and iconology statements of knowledge graphs in the semantic web (2023) 0.01 
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    Abstract
    In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects. Design/methodology/approach This study's analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians' theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures' suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness. Findings This study's results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity. Originality/value The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study's results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.
    Theme
    Semantic Web
  6. Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.01 
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    Abstract
    The lack of standardization in the production, organization and dissemination of information in documentation centers and institutions alike, as a result from the digitization of collections and their availability on the internet has called for integration efforts. The sheer availability of multimedia content has fostered the development of many distinct and, most of the time, independent metadata standards for its description. This study aims at presenting and comparing the existing standards of metadata, vocabularies and ontologies for multimedia annotation and also tries to offer a synthetic overview of its main strengths and weaknesses, aiding efforts for semantic integration and enhancing the findability of available multimedia resources on the web. We also aim at unveiling the characteristics that could, should and are perhaps not being highlighted in the characterization of multimedia resources.
  7. Frey, J.; Streitmatter, D.; Götz, F.; Hellmann, S.; Arndt, N.: DBpedia Archivo (2020) 0.00 
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    Abstract
    We are proud to announce DBpedia Archivo (https://archivo.dbpedia.org) an augmented ontology archive and interface to implement FAIRer ontologies. Each ontology is rated with 4 stars measuring basic FAIR features. We discovered 890 ontologies reaching on average 1.95 out of 4 stars. Many of them have no or unclear licenses and have issues w.r.t. retrieval and parsing.
    Content
    # Community action on individual ontologies We would like to call on all ontology maintainers and consumers to help us increase the average star rating of the web of ontologies by fixing and improving its ontologies. You can easily check an ontology at https://archivo.dbpedia.org/info. If you are an ontology maintainer just release a patched version - archivo will automatically pick it up 8 hours later. If you are a user of an ontology and want your consumed data to become FAIRer, please inform the ontology maintainer about the issues found with Archivo. The star rating is very basic and only requires fixing small things. However, theimpact on technical and legal usability can be immense.
    # Community action on all ontologies (quality, FAIRness, conformity) Archivo is extensible and allows contributions to give consumers a central place to encode their requirements. We envision fostering adherence to standards and strengthening incentives for publishers to build a better (FAIRer) web of ontologies. 1. SHACL (https://www.w3.org/TR/shacl/, co-edited by DBpedia's CTO D. Kontokostas) enables easy testing of ontologies. Archivo offers free SHACL continuous integration testing for ontologies. Anyone can implement their SHACL tests and add them to the SHACL library on Github. We believe that there are many synergies, i.e. SHACL tests for your ontology are helpful for others as well. 2. We are looking for ontology experts to join DBpedia and discuss further validation (e.g. stars) to increase FAIRness and quality of ontologies. We are forming a steering committee and also a PC for the upcoming Vocarnival at SEMANTiCS 2021. Please message hellmann@informatik.uni-leipzig.de <mailto:hellmann@informatik.uni-leipzig.de>if you would like to join. We would like to extend the Archivo platform with relevant visualisations, tests, editing aides, mapping management tools and quality checks.
    # How does Archivo work? Each week Archivo runs several discovery algorithms to scan for new ontologies. Once discovered Archivo checks them every 8 hours. When changes are detected, Archivo downloads and rates and archives the latest snapshot persistently on the DBpedia Databus. # Archivo's mission Archivo's mission is to improve FAIRness (findability, accessibility, interoperability, and reusability) of all available ontologies on the Semantic Web. Archivo is not a guideline, it is fully automated, machine-readable and enforces interoperability with its star rating. - Ontology developers can implement against Archivo until they reach more stars. The stars and tests are designed to guarantee the interoperability and fitness of the ontology. - Ontology users can better find, access and re-use ontologies. Snapshots are persisted in case the original is not reachable anymore adding a layer of reliability to the decentral web of ontologies.
  8. Auer, S.; Oelen, A.; Haris, A.M.; Stocker, M.; D'Souza, J.; Farfar, K.E.; Vogt, L.; Prinz, M.; Wiens, V.; Jaradeh, M.Y.: Improving access to scientific literature with knowledge graphs : an experiment using library guidelines to judge information integrity (2020) 0.00 
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    Abstract
    The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based-formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this article, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.
    Source
    Bibliothek: Forschung und Praxis. 44(2020) H.3, S.516-529
  9. Jansen, B.; Browne, G.M.: Navigating information spaces : index / mind map / topic map? (2021) 0.00 
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  10. Oliveira Machado, L.M.; Almeida, M.B.; Souza, R.R.: What researchers are currently saying about ontologies : a review of recent Web of Science articles (2020) 0.00 
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    Abstract
    Traditionally connected to philosophy, the term ontology is increasingly related to information systems areas. Some researchers consider the approaches of the two disciplinary contexts to be completely different. Others consider that, although different, they should talk to each other, as both seek to answer similar questions. With the extensive literature on this topic, we intend to contribute to the understanding of the use of the term ontology in current research and which references support this use. An exploratory study was developed with a mixed methodology and a sample collected from the Web of Science of articles publishe in 2018. The results show the current prevalence of computer science in studies related to ontology and also of Gruber's view suggesting ontology as kind of conceptualization, a dominant view in that field. Some researchers, particularly in the field of biomedicine, do not adhere to this dominant view but to another one that seems closer to ontological study in the philosophical context. The term ontology, in the context of information systems, appears to be consolidating with a meaning different from the original, presenting traces of the process of "metaphorization" in the transfer of the term between the two fields of study.
  11. Gladun, A.; Rogushina, J.: Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization (2021) 0.00 
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    Abstract
    We consider use of ontological background knowledge in intelligent information systems and analyze directions of their reduction in compliance with specifics of particular user task. Such reduction is aimed at simplification of knowledge processing without loss of significant information. We propose methods of generation of task thesauri based on domain ontology that contain such subset of ontological concepts and relations that can be used in task solving. Combinatorial optimization is used for minimization of task thesaurus. In this approach, semantic similarity estimates are used for determination of concept significance for user task. Some practical examples of optimized thesauri application for semantic retrieval and competence analysis demonstrate efficiency of proposed approach.
  12. Campos, L.M.: Princípios teóricos usados na elaboracao de ontologias e sua influência na recuperacao da informacao com uso de de inferências [Theoretical principles used in ontology building and their influence on information retrieval using inferences] (2021) 0.00 
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    Abstract
    Several instruments of knowledge organization will reflect different possibilities for information retrieval. In this context, ontologies have a different potential because they allow knowledge discovery, which can be used to retrieve information in a more flexible way. However, this potential can be affected by the theoretical principles adopted in ontology building. The aim of this paper is to discuss, in an introductory way, how a (not exhaustive) set of theoretical principles can influence an aspect of ontologies: their use to obtain inferences. In this context, the role of Ingetraut Dahlberg's Theory of Concept is discussed. The methodology is exploratory, qualitative, and from the technical point of view it uses bibliographic research supported by the content analysis method. It also presents a small example of application as a proof of concept. As results, a discussion about the influence of conceptual definition on subsumption inferences is presented, theoretical contributions are suggested that should be used to guide the formation of hierarchical structures on which such inferences are supported, and examples are provided of how the absence of such contributions can lead to erroneous inferences
  13. Ghosh, S.S.; Das, S.; Chatterjee, S.K.: Human-centric faceted approach for ontology construction (2020) 0.00 
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    Abstract
    In this paper, we propose an ontology building method, called human-centric faceted approach for ontology construction (HCFOC). HCFOC uses the human-centric approach, improvised with the idea of selective dissemination of information (SDI), to deal with context. Further, this ontology construction process makes use of facet analysis and an analytico-synthetic classification approach. This novel fusion contributes to the originality of HCFOC and distinguishes it from other existing ontology construction methodologies. Based on HCFOC, an ontology of the tourism domain has been designed using the Protégé-5.5.0 ontology editor. The HCFOC methodology has provided the necessary flexibility, extensibility, robustness and has facilitated the capturing of background knowledge. It models the tourism ontology in such a way that it is able to deal with the context of a tourist's information need with precision. This is evident from the result that more than 90% of the user's queries were successfully met. The use of domain knowledge and techniques from both library and information science and computer science has helped in the realization of the desired purpose of this ontology construction process. It is envisaged that HCFOC will have implications for ontology developers. The demonstrated tourism ontology can support any tourism information retrieval system.
  14. Jia, J.: From data to knowledge : the relationships between vocabularies, linked data and knowledge graphs (2021) 0.00 
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    Abstract
    Purpose The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions. Design/methodology/approach This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions. Findings Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data. Originality/value This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.
    Date
    22. 1.2021 14:24:32
  15. 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.
  16. Amirhosseini, M.; Avidan, G.: ¬A dialectic perspective on the evolution of thesauri and ontologies (2021) 0.00 
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    Abstract
    The purpose of this article is to identify the most important factors and features in the evolution of thesauri and ontologies through a dialectic model. This model relies on a dialectic process or idea which could be discovered via a dialectic method. This method has focused on identifying the logical relationship between a beginning proposition, or an idea called a thesis, a negation of that idea called the antithesis, and the result of the conflict between the two ideas, called a synthesis. During the creation of knowl­edge organization systems (KOSs), the identification of logical relations between different ideas has been made possible through the consideration and use of the most influential methods and tools such as dictionaries, Roget's Thesaurus, thesaurus, micro-, macro- and metathesauri, ontology, lower, middle and upper level ontologies. The analysis process has adapted a historical methodology, more specifically a dialectic method and documentary method as the reasoning process. This supports our arguments and synthesizes a method for the analysis of research results. Confirmed by the research results, the principle of unity has shown to be the most important factor in the development and evolution of the structure of knowl­edge organization systems and their types. There are various types of unity when considering the analysis of logical relations. These include the principle of unity of alphabetical order, unity of science, semantic unity, structural unity and conceptual unity. The results have clearly demonstrated a movement from plurality to unity in the assembling of the complex structure of knowl­edge organization systems to increase information and knowl­edge storage and retrieval performance.
  17. Broughton, V.: Science and knowledge organization : an editorial (2021) 0.00 
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    Abstract
    The purpose of this article is to identify the most important factors and features in the evolution of thesauri and ontologies through a dialectic model. This model relies on a dialectic process or idea which could be discovered via a dialectic method. This method has focused on identifying the logical relationship between a beginning proposition, or an idea called a thesis, a negation of that idea called the antithesis, and the result of the conflict between the two ideas, called a synthesis. During the creation of knowl­edge organization systems (KOSs), the identification of logical relations between different ideas has been made possible through the consideration and use of the most influential methods and tools such as dictionaries, Roget's Thesaurus, thesaurus, micro-, macro- and metathesauri, ontology, lower, middle and upper level ontologies. The analysis process has adapted a historical methodology, more specifically a dialectic method and documentary method as the reasoning process. This supports our arguments and synthesizes a method for the analysis of research results. Confirmed by the research results, the principle of unity has shown to be the most important factor in the development and evolution of the structure of knowl­edge organization systems and their types. There are various types of unity when considering the analysis of logical relations. These include the principle of unity of alphabetical order, unity of science, semantic unity, structural unity and conceptual unity. The results have clearly demonstrated a movement from plurality to unity in the assembling of the complex structure of knowl­edge organization systems to increase information and knowl­edge storage and retrieval performance.
  18. Si, L.; Zhou, J.: Ontology and linked data of Chinese great sites information resources from users' perspective (2022) 0.00 
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    Abstract
    Great Sites are closely related to the residents' life, urban and rural development. In the process of rapid urbanization in China, the protection and utilization of Great Sites are facing unprecedented pressure. Effective knowl­edge organization with ontology and linked data of Great Sites is a prerequisite for their protection and utilization. In this paper, an interview is conducted to understand the users' awareness towards Great Sites to build the user-centered ontology. As for designing the Great Site ontology, firstly, the scope of Great Sites is determined. Secondly, CIDOC- CRM and OWL-Time Ontology are reused combining the results of literature research and user interviews. Thirdly, the top-level structure and the specific instances are determined to extract knowl­edge concepts of Great Sites. Fourthly, they are transformed into classes, data properties and object properties of the Great Site ontology. Later, based on the linked data technology, taking the Great Sites in Xi'an Area as an example, this paper uses D2RQ to publish the linked data set of the knowl­edge of the Great Sites and realize its opening and sharing. Semantic services such as semantic annotation, semantic retrieval and reasoning are provided based on the ontology.
  19. Buente, W.; Baybayan, C.K.; Hajibayova, L.; McCorkhill, M.; Panchyshyn, R.: Exploring the renaissance of wayfinding and voyaging through the lens of knowledge representation, organization and discovery systems (2020) 0.00 
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    Abstract
    The purpose of this paper is to provide a critical analysis from an ethical perspective of how the concept of indigenous wayfinding and voyaging is mapped in knowledge representation, organization and discovery systems. Design/methodology/approach In this study, the Dewey Decimal Classification, the Library of Congress Subject Headings, the Library of Congress Classifications systems and the Web of Science citation database were methodically examined to determine how these systems represent and facilitate the discovery of indigenous knowledge of wayfinding and voyaging. Findings The analysis revealed that there was no dedicated representation of the indigenous practices of wayfinding and voyaging in the major knowledge representation, organization and discovery systems. By scattering indigenous practice across various, often very broad and unrelated classes, coherence in the record is disrupted, resulting in misrepresentation of these indigenous concepts. Originality/value This study contributes to a relatively limited research literature on representation and organization of indigenous knowledge of wayfinding and voyaging. This study calls to foster a better understanding and appreciation for the rich knowledge that indigenous cultures provide for an enlightened society.
    Object
    Web of Science
  20. Biagetti, M.T.: Ontologies as knowledge organization systems (2021) 0.00 
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    Abstract
    This contribution presents the principal features of ontologies, drawing special attention to the comparison between ontologies and the different kinds of know­ledge organization systems (KOS). The focus is on the semantic richness exhibited by ontologies, which allows the creation of a great number of relationships between terms. That establishes ontologies as the most evolved type of KOS. The concepts of "conceptualization" and "formalization" and the key components of ontologies are described and discussed, along with upper and domain ontologies and special typologies, such as bibliographical ontologies and biomedical ontologies. The use of ontologies in the digital libraries environment, where they have replaced thesauri for query expansion in searching, and the role they are playing in the Semantic Web, especially for semantic interoperability, are sketched.

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