Search (96 results, page 2 of 5)

  • × theme_ss:"Wissensrepräsentation"
  1. Wu, D.; Shi, J.: Classical music recording ontology used in a library catalog (2016) 0.01
    0.0075444616 = product of:
      0.03772231 = sum of:
        0.03772231 = weight(_text_:bibliographic in 3179) [ClassicSimilarity], result of:
          0.03772231 = score(doc=3179,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.21506234 = fieldWeight in 3179, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3179)
      0.2 = coord(1/5)
    
    Abstract
    In order to improve the organization of classical music information resources, we constructed a classical music recording ontology, on top of which we then designed an online classical music catalog. Our construction of the classical music recording ontology consisted of three steps: identifying the purpose, analyzing the ontology, and encoding the ontology. We identified the main classes and properties of the domain by investigating classical music recording resources and users' information needs. We implemented the ontology in the Web Ontology Language (OWL) using five steps: transforming the properties, encoding the transformed properties, defining ranges of the properties, constructing individuals, and standardizing the ontology. In constructing the online catalog, we first designed the structure and functions of the catalog based on investigations into users' information needs and information-seeking behaviors. Then we extracted classes and properties of the ontology using the Apache Jena application programming interface (API), and constructed a catalog in the Java environment. The catalog provides a hierarchical main page (built using the Functional Requirements for Bibliographic Records (FRBR) model), a classical music information network and integrated information service; this combination of features greatly eases the task of finding classical music recordings and more information about classical music.
  2. Wen, B.; Horlings, E.; Zouwen, M. van der; Besselaar, P. van den: Mapping science through bibliometric triangulation : an experimental approach applied to water research (2017) 0.01
    0.0075444616 = product of:
      0.03772231 = sum of:
        0.03772231 = weight(_text_:bibliographic in 3437) [ClassicSimilarity], result of:
          0.03772231 = score(doc=3437,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.21506234 = fieldWeight in 3437, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3437)
      0.2 = coord(1/5)
    
    Abstract
    The idea of constructing science maps based on bibliographic data has intrigued researchers for decades, and various techniques have been developed to map the structure of research disciplines. Most science mapping studies use a single method. However, as research fields have various properties, a valid map of a field should actually be composed of a set of maps derived from a series of investigations using different methods. That leads to the question of what can be learned from a combination-triangulation-of these different science maps. In this paper we propose a method for triangulation, using the example of water science. We combine three different mapping approaches: journal-journal citation relations (JJCR), shared author keywords (SAK), and title word-cited reference co-occurrence (TWRC). Our results demonstrate that triangulation of JJCR, SAK, and TWRC produces a more comprehensive picture than each method applied individually. The outcomes from the three different approaches can be associated with each other and systematically interpreted to provide insights into the complex multidisciplinary structure of the field of water research.
  3. Branch, F.; Arias, T.; Kennah, J.; Phillips, R.; Windleharth, T.; Lee, J.H.: Representing transmedia fictional worlds through ontology (2017) 0.01
    0.0075444616 = product of:
      0.03772231 = sum of:
        0.03772231 = weight(_text_:bibliographic in 3958) [ClassicSimilarity], result of:
          0.03772231 = score(doc=3958,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.21506234 = fieldWeight in 3958, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3958)
      0.2 = coord(1/5)
    
    Abstract
    Currently, there is no structured data standard for representing elements commonly found in transmedia fictional worlds. Although there are websites dedicated to individual universes, the information found on these sites separate out the various formats, concentrate on only the bibliographic aspects of the material, and are only searchable with full text. We have created an ontological model that will allow various user groups interested in transmedia to search for and retrieve the information contained in these worlds based upon their structure. We conducted a domain analysis and user studies based on the contents of Harry Potter, Lord of the Rings, the Marvel Universe, and Star Wars in order to build a new model using Ontology Web Language (OWL) and an artificial intelligence-reasoning engine. This model can infer connections between transmedia properties such as characters, elements of power, items, places, events, and so on. This model will facilitate better search and retrieval of the information contained within these vast story universes for all users interested in them. The result of this project is an OWL ontology reflecting real user needs based upon user research, which is intuitive for users and can be used by artificial intelligence systems.
  4. 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) 0.01
    0.0075444616 = product of:
      0.03772231 = sum of:
        0.03772231 = weight(_text_:bibliographic in 826) [ClassicSimilarity], result of:
          0.03772231 = score(doc=826,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.21506234 = fieldWeight in 826, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.0390625 = fieldNorm(doc=826)
      0.2 = coord(1/5)
    
    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
  5. Djioua, B.; Desclés, J.-P.; Alrahabi, M.: Searching and mining with semantic categories (2012) 0.01
    0.0070547215 = product of:
      0.035273608 = sum of:
        0.035273608 = product of:
          0.070547216 = sum of:
            0.070547216 = weight(_text_:searching in 99) [ClassicSimilarity], result of:
              0.070547216 = score(doc=99,freq=6.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38706642 = fieldWeight in 99, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=99)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Abstract
    A new model is proposed to retrieve information by building automatically a semantic metatext structure for texts that allow searching and extracting discourse and semantic information according to certain linguistic categorizations. This paper presents approaches for searching and mining full text with semantic categories. The model is built up from two engines: The first one, called EXCOM (Djioua et al., 2006; Alrahabi, 2010), is an automatic system for text annotation, related to discourse and semantic maps, which are specification of general linguistic ontologies founded on the Applicative and Cognitive Grammar. The annotation layer uses a linguistic method called Contextual Exploration, which handles the polysemic values of a term in texts. Several 'semantic maps' underlying 'point of views' for text mining guide this automatic annotation process. The second engine uses semantic annotated texts, produced previously in order to create a semantic inverted index, which is able to retrieve relevant documents for queries associated with discourse and semantic categories such as definition, quotation, causality, relations between concepts, etc. (Djioua & Desclés, 2007). This semantic indexation process builds a metatext layer for textual contents. Some data and linguistic rules sets as well as the general architecture that extend third-party software are expressed as supplementary information.
  6. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.01
    0.0061043533 = product of:
      0.030521767 = sum of:
        0.030521767 = product of:
          0.061043534 = sum of:
            0.061043534 = weight(_text_:22 in 6089) [ClassicSimilarity], result of:
              0.061043534 = score(doc=6089,freq=2.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38690117 = fieldWeight in 6089, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.078125 = fieldNorm(doc=6089)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Pages
    S.11-22
  7. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.01
    0.0061043533 = product of:
      0.030521767 = sum of:
        0.030521767 = product of:
          0.061043534 = sum of:
            0.061043534 = weight(_text_:22 in 5576) [ClassicSimilarity], result of:
              0.061043534 = score(doc=5576,freq=2.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38690117 = fieldWeight in 5576, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.078125 = fieldNorm(doc=5576)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Date
    13.12.2017 14:17:22
  8. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.01
    0.0061043533 = product of:
      0.030521767 = sum of:
        0.030521767 = product of:
          0.061043534 = sum of:
            0.061043534 = weight(_text_:22 in 539) [ClassicSimilarity], result of:
              0.061043534 = score(doc=539,freq=2.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38690117 = fieldWeight in 539, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.078125 = fieldNorm(doc=539)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Date
    26.12.2011 13:22:07
  9. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.01
    0.0061043533 = product of:
      0.030521767 = sum of:
        0.030521767 = product of:
          0.061043534 = sum of:
            0.061043534 = weight(_text_:22 in 3406) [ClassicSimilarity], result of:
              0.061043534 = score(doc=3406,freq=2.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38690117 = fieldWeight in 3406, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.078125 = fieldNorm(doc=3406)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Date
    30. 5.2010 16:22:35
  10. Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018) 0.01
    0.0061043533 = product of:
      0.030521767 = sum of:
        0.030521767 = product of:
          0.061043534 = sum of:
            0.061043534 = weight(_text_:22 in 4523) [ClassicSimilarity], result of:
              0.061043534 = score(doc=4523,freq=2.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.38690117 = fieldWeight in 4523, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.078125 = fieldNorm(doc=4523)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Source
    Spektrum der Wissenschaft. 2018, H.1, S.22-27
  11. Semantic digital libraries (2009) 0.01
    0.0060355696 = product of:
      0.030177847 = sum of:
        0.030177847 = weight(_text_:bibliographic in 3371) [ClassicSimilarity], result of:
          0.030177847 = score(doc=3371,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.17204987 = fieldWeight in 3371, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.03125 = fieldNorm(doc=3371)
      0.2 = coord(1/5)
    
    Content
    Inhalt: Introduction to Digital Libraries and Semantic Web: Introduction / Bill McDaniel and Sebastian Ryszard Kruk - Digital Libraries and Knowledge Organization / Dagobert Soergel - Semantic Web and Ontologies / Marcin Synak, Maciej Dabrowski and Sebastian Ryszard Kruk - Social Semantic Information Spaces / John G. Breslin A Vision of Semantic Digital Libraries: Goals of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel - Architecture of Semantic Digital Libraries / Sebastian Ryszard Kruk, Adam Westerki and Ewelina Kruk - Long-time Preservation / Markus Reis Ontologies for Semantic Digital Libraries: Bibliographic Ontology / Maciej Dabrowski, Macin Synak and Sebastian Ryszard Kruk - Community-aware Ontologies / Slawomir Grzonkowski, Sebastian Ryszard Kruk, Adam Gzella, Jakub Demczuk and Bill McDaniel Prototypes of Semantic Digital Libraries: JeromeDL: The Social Semantic Digital Library / Sebastian Ryszard Kruk, Mariusz Cygan, Adam Gzella, Tomasz Woroniecki and Maciej Dabrowski - The BRICKS Digital Library Infrastructure / Bernhard Haslhofer and Predrag Knezevié - Semantics in Greenstone / Annika Hinze, George Buchanan, David Bainbridge and Ian Witten Building the Future - Semantic Digital Libraries in Use: Hyperbooks / Gilles Falquet, Luka Nerima and Jean-Claude Ziswiler - Semantic Digital Libraries for Archiving / Bill McDaniel - Evaluation of Semantic and Social Technologies for Digital Libraries / Sebastian Ryszard Kruk, Ewelina Kruk and Katarzyna Stankiewicz - Conclusions: The Future of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel
  12. Baker, T.; Bermès, E.; Coyle, K.; Dunsire, G.; Isaac, A.; Murray, P.; Panzer, M.; Schneider, J.; Singer, R.; Summers, E.; Waites, W.; Young, J.; Zeng, M.: Library Linked Data Incubator Group Final Report (2011) 0.01
    0.0060355696 = product of:
      0.030177847 = sum of:
        0.030177847 = weight(_text_:bibliographic in 4796) [ClassicSimilarity], result of:
          0.030177847 = score(doc=4796,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.17204987 = fieldWeight in 4796, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.03125 = fieldNorm(doc=4796)
      0.2 = coord(1/5)
    
    Abstract
    The mission of the W3C Library Linked Data Incubator Group, chartered from May 2010 through August 2011, has been "to help increase global interoperability of library data on the Web, by bringing together people involved in Semantic Web activities - focusing on Linked Data - in the library community and beyond, building on existing initiatives, and identifying collaboration tracks for the future." In Linked Data [LINKEDDATA], data is expressed using standards such as Resource Description Framework (RDF) [RDF], which specifies relationships between things, and Uniform Resource Identifiers (URIs, or "Web addresses") [URI]. This final report of the Incubator Group examines how Semantic Web standards and Linked Data principles can be used to make the valuable information assets that library create and curate - resources such as bibliographic data, authorities, and concept schemes - more visible and re-usable outside of their original library context on the wider Web. The Incubator Group began by eliciting reports on relevant activities from parties ranging from small, independent projects to national library initiatives (see the separate report, Library Linked Data Incubator Group: Use Cases) [USECASE]. These use cases provided the starting point for the work summarized in the report: an analysis of the benefits of library Linked Data, a discussion of current issues with regard to traditional library data, existing library Linked Data initiatives, and legal rights over library data; and recommendations for next steps. The report also summarizes the results of a survey of current Linked Data technologies and an inventory of library Linked Data resources available today (see also the more detailed report, Library Linked Data Incubator Group: Datasets, Value Vocabularies, and Metadata Element Sets) [VOCABDATASET].
  13. Boteram, F.: "Content architecture" : semantic interoperability in an international comprehensive knowledge organisation system (2010) 0.01
    0.0060355696 = product of:
      0.030177847 = sum of:
        0.030177847 = weight(_text_:bibliographic in 647) [ClassicSimilarity], result of:
          0.030177847 = score(doc=647,freq=2.0), product of:
            0.17540175 = queryWeight, product of:
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.045055166 = queryNorm
            0.17204987 = fieldWeight in 647, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.893044 = idf(docFreq=2449, maxDocs=44218)
              0.03125 = fieldNorm(doc=647)
      0.2 = coord(1/5)
    
    Abstract
    Purpose - This paper seeks to develop a specified typology of various levels of semantic interoperability, designed to provide semantically expressive and functional means to interconnect typologically different sub-systems in an international comprehensive knowledge organization system, supporting advanced information retrieval and exploration strategies. Design/methodology/approach - Taking the analysis of rudimentary forms of a functional interoperability based on simple pattern matching as a starting-point, more refined strategies to provide semantic interoperability, which is actually reaching the conceptual and even thematic level, are being developed. The paper also examines the potential benefits and perspectives of the selective transfer of modelling strategies from the field of semantic technologies for the refinement of relational structures of inter-system and inter-concept relations as a requirement for expressive and functional indexing languages supporting advanced types of semantic interoperability. Findings - As the principles and strategies of advanced information retrieval systems largely depend on semantic information, new concepts and strategies to achieve semantic interoperability have to be developed. Research limitations/implications - The approach has been developed in the functional and structural context of an international comprehensive system integrating several heterogeneous knowledge organization systems and indexing languages by interconnecting them to a central conceptual structure operating as a spine in an overall system designed to support retrieval and exploration of bibliographic records representing complex conceptual entities. Originality/value - Research and development aimed at providing technical and structural interoperability has to be complemented by a thorough and precise reflection and definition of various degrees and types of interoperability on the semantic level as well. The approach specifies these levels and reflects the implications and their potential for advanced strategies of retrieval and exploration.
  14. Saruladha, K.; Aghila, G.; Penchala, S.K.: Design of new indexing techniques based on ontology for information retrieval systems (2010) 0.01
    0.005760156 = product of:
      0.02880078 = sum of:
        0.02880078 = product of:
          0.05760156 = sum of:
            0.05760156 = weight(_text_:searching in 4317) [ClassicSimilarity], result of:
              0.05760156 = score(doc=4317,freq=4.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.3160384 = fieldWeight in 4317, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4317)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Abstract
    Information Retrieval [IR] is the science of searching for documents, for information within documents, and for metadata about documents, as well as that of searching relational databases and the World Wide Web. This paper describes a document representation method instead of keywords ontological descriptors. The purpose of this paper is to propose a system for content-based querying of texts based on the availability of ontology for the concepts in the text domain and to develop new Indexing methods to improve RSV (Retrieval status value). There is a need for querying ontologies at various granularities to retrieve information from various sources to suit the requirements of Semantic web, to eradicate the mismatch between user request and response from the Information Retrieval system. Most of the search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. The indexes do not contain synonyms, cannot differentiate between homonyms and users receive different search results when they use different conjugation forms of the same word.
  15. Biagetti, M.T.: Ontologies as knowledge organization systems (2021) 0.01
    0.0057022637 = product of:
      0.028511317 = sum of:
        0.028511317 = product of:
          0.057022635 = sum of:
            0.057022635 = weight(_text_:searching in 439) [ClassicSimilarity], result of:
              0.057022635 = score(doc=439,freq=2.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.31286204 = fieldWeight in 439, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=439)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    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.
  16. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.01
    0.0057022637 = product of:
      0.028511317 = sum of:
        0.028511317 = product of:
          0.057022635 = sum of:
            0.057022635 = weight(_text_:searching in 667) [ClassicSimilarity], result of:
              0.057022635 = score(doc=667,freq=2.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.31286204 = fieldWeight in 667, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=667)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    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.
  17. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.01
    0.005179716 = product of:
      0.02589858 = sum of:
        0.02589858 = product of:
          0.05179716 = sum of:
            0.05179716 = weight(_text_:22 in 3355) [ClassicSimilarity], result of:
              0.05179716 = score(doc=3355,freq=4.0), product of:
                0.15777552 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045055166 = queryNorm
                0.32829654 = fieldWeight in 3355, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3355)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  18. Wang, H.; Liu, Q.; Penin, T.; Fu, L.; Zhang, L.; Tran, T.; Yu, Y.; Pan, Y.: Semplore: a scalable IR approach to search the Web of Data (2009) 0.00
    0.0048876544 = product of:
      0.024438271 = sum of:
        0.024438271 = product of:
          0.048876543 = sum of:
            0.048876543 = weight(_text_:searching in 1638) [ClassicSimilarity], result of:
              0.048876543 = score(doc=1638,freq=2.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.26816747 = fieldWeight in 1638, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.046875 = fieldNorm(doc=1638)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Abstract
    The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.
  19. Yi, M.: Information organization and retrieval using a topic maps-based ontology : results of a task-based evaluation (2008) 0.00
    0.0048876544 = product of:
      0.024438271 = sum of:
        0.024438271 = product of:
          0.048876543 = sum of:
            0.048876543 = weight(_text_:searching in 2369) [ClassicSimilarity], result of:
              0.048876543 = score(doc=2369,freq=2.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.26816747 = fieldWeight in 2369, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2369)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Abstract
    As information becomes richer and more complex, alternative information-organization methods are needed to more effectively and efficiently retrieve information from various systems, including the Web. The objective of this study is to explore how a Topic Maps-based ontology approach affects users' searching performance. Forty participants participated in a task-based evaluation where two dependent variables, recall and search time, were measured. The results of this study indicate that a Topic Maps-based ontology information retrieval (TOIR) system has a significant and positive effect on both recall and search time, compared to a thesaurus-based information retrieval (TIR) system. These results suggest that the inclusion of a Topic Maps-based ontology is a beneficial approach to take when designing information retrieval systems.
  20. Davies, J.; Weeks, R.; Krohn, U.: QuizRDF: search technology for the Semantic Web (2004) 0.00
    0.0048876544 = product of:
      0.024438271 = sum of:
        0.024438271 = product of:
          0.048876543 = sum of:
            0.048876543 = weight(_text_:searching in 4316) [ClassicSimilarity], result of:
              0.048876543 = score(doc=4316,freq=2.0), product of:
                0.18226127 = queryWeight, product of:
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.045055166 = queryNorm
                0.26816747 = fieldWeight in 4316, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.0452914 = idf(docFreq=2103, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4316)
          0.5 = coord(1/2)
      0.2 = coord(1/5)
    
    Abstract
    An information-seeking system is described which combines traditional keyword querying of WWW resources with the ability to browse and query against RDF annotations of those resources. RDF(S) and RDF are used to specify and populate an ontology and the resultant RDF annotations are then indexed along with the full text of the annotated resources. The resultant index allows both keyword querying against the full text of the document and the literal values occurring in the RDF annotations, along with the ability to browse and query the ontology. We motivate our approach as a key enabler for fully exploiting the Semantic Web in the area of knowledge management and argue that the ability to combine searching and browsing behaviours more fully supports a typical information-seeking task. The approach is characterised as "low threshold, high ceiling" in the sense that where RDF annotations exist they are exploited for an improved information-seeking experience but where they do not yet exist, a search capability is still available.

Years

Languages

  • e 79
  • d 13
  • pt 1
  • More… Less…

Types

  • a 73
  • el 20
  • x 8
  • m 4
  • n 2
  • r 1
  • s 1
  • More… Less…