Search (116 results, page 1 of 6)

0.0719772 = product of:
  0.1079658 = sum of:
    0.08467446 = product of:
      0.25402337 = sum of:
        0.25402337 = weight(_text_:objects in 680) [ClassicSimilarity], result of:
          0.25402337 = score(doc=680,freq=16.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.83047986 = fieldWeight in 680, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.0390625 = fieldNorm(doc=680)
      0.33333334 = coord(1/3)
    0.023291335 = product of:
      0.04658267 = sum of:
        0.04658267 = weight(_text_:indexing in 680) [ClassicSimilarity], result of:
          0.04658267 = score(doc=680,freq=2.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.21146181 = fieldWeight in 680, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=680)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

In this article, we investigate what sorts of information humans request about geographical objects of the same type. For example, Edinburgh Castle and Bodiam Castle are two objects of the same type: "castle." The question is whether specific information is requested for the object type "castle" and how this information differs for objects of other types (e.g., church, museum, or lake). We aim to answer this question using an online survey. In the survey, we showed 184 participants 200 images pertaining to urban and rural objects and asked them to write questions for which they would like to know the answers when seeing those objects. Our analysis of the 6,169 questions collected in the survey shows that humans have shared ideas of what to ask about geographical objects. When the object types resemble each other (e.g., church and temple), the requested information is similar for the objects of these types. Otherwise, the information is specific to an object type. Our results may be very useful in guiding Natural Language Processing tasks involving automatic generation of templates for image descriptions and their assessment, as well as image indexing and organization.

0.06614321 = product of:
  0.09921481 = sum of:
    0.050804675 = product of:
      0.15241402 = sum of:
        0.15241402 = weight(_text_:objects in 4318) [ClassicSimilarity], result of:
          0.15241402 = score(doc=4318,freq=4.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.49828792 = fieldWeight in 4318, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.046875 = fieldNorm(doc=4318)
      0.33333334 = coord(1/3)
    0.04841013 = product of:
      0.09682026 = sum of:
        0.09682026 = weight(_text_:indexing in 4318) [ClassicSimilarity], result of:
          0.09682026 = score(doc=4318,freq=6.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.4395151 = fieldWeight in 4318, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.046875 = fieldNorm(doc=4318)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

This paper presents a novel hybrid approach for visual information retrieval (VIR) that combines shape analysis of objects in image with their indexing by textual descriptions. The principal goal of presented technique is applying Two Segments Turning Function (2STF) proposed by authors for efficient invariant to spatial variations shape processing and implementation of semantic Web approaches for ontology-based user-oriented annotations of multimedia information. In the proposed approach the user's textual queries are converted to image features, which are used for images searching, indexing, interpretation, and retrieval. A decision about similarity between retrieved image and user's query is taken computing the shape convergence to 2STF combining it with matching the ontological annotations of objects in image and providing in this way automatic definition of the machine-understandable semantics. In order to evaluate the proposed approach the Image Retrieval by Ontological Description of Shapes system has been designed and tested using some standard image domains.

0.052860245 = product of:
  0.15858074 = sum of:
    0.15858074 = sum of:
      0.11179841 = weight(_text_:indexing in 987) [ClassicSimilarity], result of:
        0.11179841 = score(doc=987,freq=8.0), product of:
          0.2202888 = queryWeight, product of:
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.057548698 = queryNorm
          0.5075084 = fieldWeight in 987, product of:
            2.828427 = tf(freq=8.0), with freq of:
              8.0 = termFreq=8.0
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.046875 = fieldNorm(doc=987)
      0.046782322 = weight(_text_:22 in 987) [ClassicSimilarity], result of:
        0.046782322 = score(doc=987,freq=2.0), product of:
          0.20152573 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.057548698 = queryNorm
          0.23214069 = fieldWeight in 987, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=987)
  0.33333334 = coord(1/3)

Abstract

This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve languages as a tool for subject queries and knowledge exploration. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.

Content

Introduction: envisioning semantic information spacesIndexing and knowledge organization -- Semantic technologies for knowledge representation -- Information retrieval and knowledge exploration -- Approaches to handle heterogeneity -- Problems with establishing semantic interoperability -- Formalization in indexing languages -- Typification of semantic relations -- Inferences in retrieval processes -- Semantic interoperability and inferences -- Remaining research questions.

Date

23. 7.2017 13:49:22

LCSH

Indexing

Subject

Indexing

0.051595338 = product of:
  0.154786 = sum of:
    0.154786 = sum of:
      0.12359779 = weight(_text_:indexing in 4399) [ClassicSimilarity], result of:
        0.12359779 = score(doc=4399,freq=22.0), product of:
          0.2202888 = queryWeight, product of:
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.057548698 = queryNorm
          0.56107163 = fieldWeight in 4399, product of:
            4.690416 = tf(freq=22.0), with freq of:
              22.0 = termFreq=22.0
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.03125 = fieldNorm(doc=4399)
      0.031188216 = weight(_text_:22 in 4399) [ClassicSimilarity], result of:
        0.031188216 = score(doc=4399,freq=2.0), product of:
          0.20152573 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.057548698 = queryNorm
          0.15476047 = fieldWeight in 4399, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.03125 = fieldNorm(doc=4399)
  0.33333334 = coord(1/3)

Abstract

Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
Modular ontologies are built in modular manner by combining modules from multiple relevant ontologies. Ontology heterogeneity also arises during modular ontology construction because multiple ontologies are being dealt with, during this process. Ontologies need to be aligned before using them for modular ontology construction. The existing approaches for ontology alignment compare all the concepts of each ontology to be aligned, hence not optimized in terms of time and search space utilization. A new indexing technique is proposed based on modular ontology. An efficient ontology alignment technique is proposed to solve the heterogeneity problem during the construction of modular ontology. Results are satisfactory as Precision and Recall are improved by (8%) and (10%) respectively. The value of Pearsons Correlation Coefficient for degree of similarity, time, search space requirement, precision and recall are close to 1 which shows that the results are significant. Further research can be carried out for using modular ontology based indexing technique for Multimedia Information Retrieval and Bio-Medical information retrieval.

Date

20. 1.2015 18:30:22

0.046134274 = product of:
  0.06920141 = sum of:
    0.041911718 = product of:
      0.12573515 = sum of:
        0.12573515 = weight(_text_:objects in 1437) [ClassicSimilarity], result of:
          0.12573515 = score(doc=1437,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.41106653 = fieldWeight in 1437, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1437)
      0.33333334 = coord(1/3)
    0.027289689 = product of:
      0.054579377 = sum of:
        0.054579377 = weight(_text_:22 in 1437) [ClassicSimilarity], result of:
          0.054579377 = score(doc=1437,freq=2.0), product of:
            0.20152573 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.057548698 = queryNorm
            0.2708308 = fieldWeight in 1437, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1437)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

This paper describes to construct faceted ontologies for domain modeling. Building upon the faceted theory of S.R. Ranganathan (1967), the paper intends to address the faceted classification approach applied to build domain ontologies. As classificatory ontologies are employed to represent the relationships of entities and objects on the web, the faceted approach helps to analyze domain representation in an effective way for modeling. Based on this perspective, an ontology of the music domain has been analyzed that would serve as a case study.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

0.046134274 = product of:
  0.06920141 = sum of:
    0.041911718 = product of:
      0.12573515 = sum of:
        0.12573515 = weight(_text_:objects in 2654) [ClassicSimilarity], result of:
          0.12573515 = score(doc=2654,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.41106653 = fieldWeight in 2654, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2654)
      0.33333334 = coord(1/3)
    0.027289689 = product of:
      0.054579377 = sum of:
        0.054579377 = weight(_text_:22 in 2654) [ClassicSimilarity], result of:
          0.054579377 = score(doc=2654,freq=2.0), product of:
            0.20152573 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.057548698 = queryNorm
            0.2708308 = fieldWeight in 2654, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2654)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.

Date

22. 1.2016 17:30:31

0.040810462 = product of:
  0.06121569 = sum of:
    0.023949554 = product of:
      0.07184866 = sum of:
        0.07184866 = weight(_text_:objects in 2281) [ClassicSimilarity], result of:
          0.07184866 = score(doc=2281,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.23489517 = fieldWeight in 2281, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.03125 = fieldNorm(doc=2281)
      0.33333334 = coord(1/3)
    0.037266135 = product of:
      0.07453227 = sum of:
        0.07453227 = weight(_text_:indexing in 2281) [ClassicSimilarity], result of:
          0.07453227 = score(doc=2281,freq=8.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.3383389 = fieldWeight in 2281, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.03125 = fieldNorm(doc=2281)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

An information system like the Web is a continuously evolving system consisting of multiple heterogeneous information sources, covering a wide domain of discourse, and a huge number of users (human or software) with diverse characteristics and needs, that produce and consume information. The challenge nowadays is to build a scalable information infrastructure enabling the effective, accurate, content based retrieval of information, in a way that adapts to the characteristics and interests of the users. The aim of this work is to propose formally sound methods for building such an information network based on ontologies which are widely used and are easy to grasp by ordinary Web users. The main results of this work are: - A novel scheme for indexing and retrieving objects according to multiple aspects or facets. The proposed scheme is a faceted scheme enriched with a method for specifying the combinations of terms that are valid. We give a model-theoretic interpretation to this model and we provide mechanisms for inferring the valid combinations of terms. This inference service can be exploited for preventing errors during the indexing process, which is very important especially in the case where the indexing is done collaboratively by many users, and for deriving "complete" navigation trees suitable for browsing through the Web. The proposed scheme has several advantages over the hierarchical classification schemes currently employed by Web catalogs, namely, conceptual clarity (it is easier to understand), compactness (it takes less space), and scalability (the update operations can be formulated more easily and be performed more effciently). - A exible and effecient model for building mediators over ontology based information sources. The proposed mediators support several modes of query translation and evaluation which can accommodate various application needs and levels of answer quality. The proposed model can be used for providing users with customized views of Web catalogs. It can also complement the techniques for building mediators over relational sources so as to support approximate translation of partially ordered domain values.

0.039543662 = product of:
  0.05931549 = sum of:
    0.03592433 = product of:
      0.10777299 = sum of:
        0.10777299 = weight(_text_:objects in 2418) [ClassicSimilarity], result of:
          0.10777299 = score(doc=2418,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.35234275 = fieldWeight in 2418, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.046875 = fieldNorm(doc=2418)
      0.33333334 = coord(1/3)
    0.023391161 = product of:
      0.046782322 = sum of:
        0.046782322 = weight(_text_:22 in 2418) [ClassicSimilarity], result of:
          0.046782322 = score(doc=2418,freq=2.0), product of:
            0.20152573 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.057548698 = queryNorm
            0.23214069 = fieldWeight in 2418, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2418)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Integrated digital access to multiple collections is a prominent issue for many Cultural Heritage institutions. The metadata describing diverse collections must be interoperable, which requires aligning the controlled vocabularies that are used to annotate objects from these collections. In this paper, we present an experiment where we match the vocabularies of two collections by applying the Knowledge Representation techniques established in recent Semantic Web research. We discuss the steps that are required for such matching, namely formalising the initial resources using Semantic Web languages, and running ontology mapping tools on the resulting representations. In addition, we present a prototype that enables the user to browse the two collections using the obtained alignment while still providing her with the original vocabulary structures.

Source

Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006

0.039543662 = product of:
  0.05931549 = sum of:
    0.03592433 = product of:
      0.10777299 = sum of:
        0.10777299 = weight(_text_:objects in 2623) [ClassicSimilarity], result of:
          0.10777299 = score(doc=2623,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.35234275 = fieldWeight in 2623, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.046875 = fieldNorm(doc=2623)
      0.33333334 = coord(1/3)
    0.023391161 = product of:
      0.046782322 = sum of:
        0.046782322 = weight(_text_:22 in 2623) [ClassicSimilarity], result of:
          0.046782322 = score(doc=2623,freq=2.0), product of:
            0.20152573 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.057548698 = queryNorm
            0.23214069 = fieldWeight in 2623, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2623)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Contemporary retrieval systems, which search across collections, usually ignore collection-level metadata. Alternative approaches, exploiting collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection/item metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata creators describing objects, and (iii) system designers implementing systems that take advantage of collection-level metadata. We present three examples of collection/item metadata relationship categories, attribute/value-propagation, value-propagation, and value-constraint and show that even in these simple cases a precise formulation requires modal notions in addition to first-order logic. These formulations are related to recent work in information retrieval and ontology evaluation.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.039543662 = product of:
  0.05931549 = sum of:
    0.03592433 = product of:
      0.10777299 = sum of:
        0.10777299 = weight(_text_:objects in 3387) [ClassicSimilarity], result of:
          0.10777299 = score(doc=3387,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.35234275 = fieldWeight in 3387, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.046875 = fieldNorm(doc=3387)
      0.33333334 = coord(1/3)
    0.023391161 = product of:
      0.046782322 = sum of:
        0.046782322 = weight(_text_:22 in 3387) [ClassicSimilarity], result of:
          0.046782322 = score(doc=3387,freq=2.0), product of:
            0.20152573 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.057548698 = queryNorm
            0.23214069 = fieldWeight in 3387, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3387)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.

Date

1. 8.2010 12:35:22

0.03548552 = product of:
  0.053228278 = sum of:
    0.029936943 = product of:
      0.089810826 = sum of:
        0.089810826 = weight(_text_:objects in 259) [ClassicSimilarity], result of:
          0.089810826 = score(doc=259,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.29361898 = fieldWeight in 259, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.0390625 = fieldNorm(doc=259)
      0.33333334 = coord(1/3)
    0.023291335 = product of:
      0.04658267 = sum of:
        0.04658267 = weight(_text_:indexing in 259) [ClassicSimilarity], result of:
          0.04658267 = score(doc=259,freq=2.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.21146181 = fieldWeight in 259, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=259)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

The paper presents the possibilities offered by poly-hierarchical conceptual structures as knowledge organizers, starting from the FRBR entity-relation model. Of the ten entities defined in the FRBR model, the first six, the bibliographic entities plus those representing the intellectual responsibilities, are clearly described by their attributes. Unlike those the other four representing subjects in their own right: concepts, objects, events and places only have the term for the entity as attribute. Subjects have to be more extensively treated in a revised version of the FRBR model, with particular attention for the semantic and syntactic relations between concepts representing subjects themselves and between these concepts and terms used in indexing. The conceptual model of poly-hierarchical thesauri is regarded as an entity-relation model, one capable to accommodate both conceptually and relationally subjects in the bibliographic universe. Polyhierarchical thesauri are considered as frameworks or templates meant to enhance knowledge representation and to support information searching.

0.03548552 = product of:
  0.053228278 = sum of:
    0.029936943 = product of:
      0.089810826 = sum of:
        0.089810826 = weight(_text_:objects in 1395) [ClassicSimilarity], result of:
          0.089810826 = score(doc=1395,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.29361898 = fieldWeight in 1395, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1395)
      0.33333334 = coord(1/3)
    0.023291335 = product of:
      0.04658267 = sum of:
        0.04658267 = weight(_text_:indexing in 1395) [ClassicSimilarity], result of:
          0.04658267 = score(doc=1395,freq=2.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.21146181 = fieldWeight in 1395, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1395)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

This paper focuses on the discursive formations emerging from the Social Semantic Information Spaces (SSIS) in light of the concept of emergence in the theory of integrative levels. The study aims to identify the opportunities and challenges of incorporating epistemological considerations in the act of acquiring knowledge into the consolidation of knowledge organization and mediation processes and devices in the emergence of phenomena. The goal was to analyze the effects of that concept on the actions of a sample of researchers registered in an emerging research domain in SSIS in order to understand this type of indexing done by the users and communities as a classification of integrating levels. The methodology was established by triangulation through social network analysis, consensus analysis and archaeology of knowledge. It was possible to conclude that there is a collective effort to settle a semantic interoperability model for the labeling of contents based on best practices regarding the description of the objects shared in SSIS.

0.032796737 = product of:
  0.049195103 = sum of:
    0.020955859 = product of:
      0.062867574 = sum of:
        0.062867574 = weight(_text_:objects in 1782) [ClassicSimilarity], result of:
          0.062867574 = score(doc=1782,freq=2.0), product of:
            0.30587542 = queryWeight, product of:
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.057548698 = queryNorm
            0.20553327 = fieldWeight in 1782, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.315071 = idf(docFreq=590, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1782)
      0.33333334 = coord(1/3)
    0.028239243 = product of:
      0.056478485 = sum of:
        0.056478485 = weight(_text_:indexing in 1782) [ClassicSimilarity], result of:
          0.056478485 = score(doc=1782,freq=6.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.25638384 = fieldWeight in 1782, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1782)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Logic and the Organization of Information closely examines the historical and contemporary methodologies used to catalogue information objects-books, ebooks, journals, articles, web pages, images, emails, podcasts and more-in the digital era. This book provides an in-depth technical background for digital librarianship, and covers a broad range of theoretical and practical topics including: classification theory, topic annotation, automatic clustering, generalized synonymy and concept indexing, distributed libraries, semantic web ontologies and Simple Knowledge Organization System (SKOS). It also analyzes the challenges facing today's information architects, and outlines a series of techniques for overcoming them. Logic and the Organization of Information is intended for practitioners and professionals working at a design level as a reference book for digital librarianship. Advanced-level students, researchers and academics studying information science, library science, digital libraries and computer science will also find this book invaluable.

Footnote

Rez. in: J. Doc. 70(2014) no.4: "Books on the organization of information and knowledge, aimed at a library/information audience, tend to fall into two clear categories. Most are practical and pragmatic, explaining the "how" as much or more than the "why". Some are theoretical, in part or in whole, showing how the practice of classification, indexing, resource description and the like relates to philosophy, logic, and other foundational bases; the books by Langridge (1992) and by Svenonious (2000) are well-known examples this latter kind. To this category certainly belongs a recent book by Martin Frické (2012). The author takes the reader for an extended tour through a variety of aspects of information organization, including classification and taxonomy, alphabetical vocabularies and indexing, cataloguing and FRBR, and aspects of the semantic web. The emphasis throughout is on showing how practice is, or should be, underpinned by formal structures; there is a particular emphasis on first order predicate calculus. The advantages of a greater, and more explicit, use of symbolic logic is a recurring theme of the book. There is a particularly commendable historical dimension, often omitted in texts on this subject. It cannot be said that this book is entirely an easy read, although it is well written with a helpful index, and its arguments are generally well supported by clear and relevant examples. It is thorough and detailed, but thereby seems better geared to the needs of advanced students and researchers than to the practitioners who are suggested as a main market. For graduate students in library/information science and related disciplines, in particular, this will be a valuable resource. I would place it alongside Svenonious' book as the best insight into the theoretical "why" of information organization. It has evoked a good deal of interest, including a set of essay commentaries in Journal of Information Science (Gilchrist et al., 2013). Introducing these, Alan Gilchrist rightly says that Frické deserves a salute for making explicit the fundamental relationship between the ancient discipline of logic and modern information organization. If information science is to continue to develop, and make a contribution to the organization of the information environments of the future, then this book sets the groundwork for the kind of studies which will be needed." (D. Bawden)

0.032288767 = product of:
  0.0968663 = sum of:
    0.0968663 = weight(_text_:systematik in 3894) [ClassicSimilarity], result of:
      0.0968663 = score(doc=3894,freq=2.0), product of:
        0.355158 = queryWeight, product of:
          6.1714344 = idf(docFreq=250, maxDocs=44218)
          0.057548698 = queryNorm
        0.27274144 = fieldWeight in 3894, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.1714344 = idf(docFreq=250, maxDocs=44218)
          0.03125 = fieldNorm(doc=3894)
  0.33333334 = coord(1/3)

Abstract

AGI - Information Management Consultants liefern seit nunmehr 16 Jahren eine Software zur Entwicklung von Thesauri und Klassifikationen, ehemals bezeichnet als INDEX, seit zweieinhalb Jahren als IC INDEX neu entwickelt. Solche Terminologien werden oft auch als Glossar, Lexikon, Topic Maps, RDF, semantisches Netz, Systematik, Aktenplan oder Nomenklatur bezeichnet. Die Software erlaubt zwar schon immer, dass solche terminologischen Werke mehrsprachig angelegt sind, doch es gab keine speziellen Werkzeuge, um die Übersetzung zu erleichtern. Die Globalisierung führt zunehmend auch zur Mehrsprachigkeit von Fachterminologien, wie laufende Projekte belegen. In IC INDEX 5.08 wurde deshalb ein spezieller Workflow für die Übersetzung implementiert, der Wortfelder bearbeitet und dabei weitgehend automatisch, aber vom Übersetzer kontrolliert, die richtigen Verbindungen zwischen den Termen in den anderen Sprachen erzeugt. Bereits dieser Workflow beschleunigt wesentlich die Übersetzungstätigkeit. Doch es geht noch schneller: der eTranslation Server von Linguatec generiert automatisch Übersetzungsvorschläge für Deutsch/English und Deutsch/Französisch. Demnächst auch Deutsch/Spanisch und Deutsch/Italienisch. Gerade bei Mehrwortbegriffen, Klassenbezeichnungen und Komposita spielt die automatische Übersetzung gegenüber dem Wörterbuch-Lookup ihre Stärke aus. Der Rückgriff ins Wörterbuch ist selbstverständlich auch implementiert, sowohl auf das Linguatec-Wörterbuch und zusätzlich jedes beliebige über eine URL adressierbare Wörterbuch. Jeder Übersetzungsvorschlag muss vom Terminologie-Entwickler bestätigt werden. Im Rahmen der Oualitätskontrolle haben wir anhand vorliegender mehrsprachiger Thesauri getestet mit dem Ergebnis, dass die automatischen Vorschläge oft gleich und fast immer sehr nahe an der gewünschten Übersetzung waren. Worte, die für durchschnittlich gebildete Menschen nicht mehr verständlich sind, bereiten auch der maschinellen Übersetzung Probleme, z.B. Fachbegriffe aus Medizin, Chemie und anderen Wissenschaften. Aber auch ein Humanübersetzer wäre hier ohne einschlägige Fachausbildung überfordert. Also, ohne Fach- und ohne Sprachkompetenz geht es nicht, aber mit geht es ziemlich flott. IC INDEX basiert auf Lotus Notes & Domino 5.08. Beliebige Relationen zwischen Termen sind zulässig, die ANSI-Normen sind implementiert und um zusätzliche Relationen ergänzt, 26 Relationen gehören zum Lieferumfang. Ausgaben gemäß Topic Maps oder RDF - zwei eng verwandte Normen-werden bei Nachfrage entwickelt. Ausgaben sind in HMTL, XML, eine ansprechende Druckversion unter MS Word 2000 und für verschiedene Search-Engines vorhanden. AGI - Information Management Consultants, Neustadt an der Weinstraße, beraten seit 1983 Unternehmen und Organisationen im dem heute als Knowledge Management bezeichneten Feld. Seit 1994 liefern sie eine umfassende, hochintegrative Lösung: "Information Center" - darin ist IC INDEX ein eigenständiges Modul zur Unterstützung von mehrsprachiger Indexierung und mehrsprachigem semantischem Retrieval. Linguatec, München, ist einstmals aus den linguistischen Forschungslabors von IBM hervorgegangen und ist über den Personal Translator weithin bekannt.

0.03046753 = product of:
  0.09140259 = sum of:
    0.09140259 = product of:
      0.27420777 = sum of:
        0.27420777 = weight(_text_:3a in 400) [ClassicSimilarity], result of:
          0.27420777 = score(doc=400,freq=2.0), product of:
            0.4878985 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.057548698 = queryNorm
            0.56201804 = fieldWeight in 400, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.046875 = fieldNorm(doc=400)
      0.33333334 = coord(1/3)
  0.33333334 = coord(1/3)

Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

0.027922725 = product of:
  0.083768174 = sum of:
    0.083768174 = sum of:
      0.056478485 = weight(_text_:indexing in 1633) [ClassicSimilarity], result of:
        0.056478485 = score(doc=1633,freq=6.0), product of:
          0.2202888 = queryWeight, product of:
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.057548698 = queryNorm
          0.25638384 = fieldWeight in 1633, product of:
            2.4494898 = tf(freq=6.0), with freq of:
              6.0 = termFreq=6.0
            3.8278677 = idf(docFreq=2614, maxDocs=44218)
            0.02734375 = fieldNorm(doc=1633)
      0.027289689 = weight(_text_:22 in 1633) [ClassicSimilarity], result of:
        0.027289689 = score(doc=1633,freq=2.0), product of:
          0.20152573 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.057548698 = queryNorm
          0.1354154 = fieldWeight in 1633, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.02734375 = fieldNorm(doc=1633)
  0.33333334 = coord(1/3)

Abstract

Purpose - The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts. Design/methodology/approach - In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query. Findings - The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology "with and without query expansion" is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42. Practical implications - When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved. Originality/value - In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.

Date

20. 1.2015 18:30:22

0.024844091 = product of:
  0.07453227 = sum of:
    0.07453227 = product of:
      0.14906454 = sum of:
        0.14906454 = weight(_text_:indexing in 1510) [ClassicSimilarity], result of:
          0.14906454 = score(doc=1510,freq=8.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.6766778 = fieldWeight in 1510, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0625 = fieldNorm(doc=1510)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Starting from an unsolved problem of information retrieval this paper presents an ontology-based model for indexing and retrieval. The model combines the methods and experiences of cognitive-to-interpret indexing languages with the strengths and possibilities of formal knowledge representation. The core component of the model uses inferences along the paths of typed relations between the entities of a knowledge representation for enabling the determination of hit quantities in the context of retrieval processes. The entities are arranged in aspect-oriented facets to ensure a consistent hierarchical structure. The possible consequences for indexing and retrieval are discussed.

0.02173858 = product of:
  0.06521574 = sum of:
    0.06521574 = product of:
      0.13043147 = sum of:
        0.13043147 = weight(_text_:indexing in 2777) [ClassicSimilarity], result of:
          0.13043147 = score(doc=2777,freq=8.0), product of:
            0.2202888 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.057548698 = queryNorm
            0.5920931 = fieldWeight in 2777, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2777)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

The presented ontology-based model for indexing and retrieval combines the methods and experiences of traditional indexing languages with their cognitively interpreted entities and relationships with the strengths and possibilities of formal knowledge representation. The core component of the model uses inferences along the paths of typed relations between the entities of a knowledge representation for enabling the determination of result sets in the context of retrieval processes. A proposal for a general, but condensed, inventory of typed relations is given. The entities are arranged in aspect-oriented facets to ensure a consistent hierarchical structure. The possible consequences for indexing and retrieval are discussed.

0.020311687 = product of:
  0.06093506 = sum of:
    0.06093506 = product of:
      0.18280518 = sum of:
        0.18280518 = weight(_text_:3a in 701) [ClassicSimilarity], result of:
          0.18280518 = score(doc=701,freq=2.0), product of:
            0.4878985 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.057548698 = queryNorm
            0.3746787 = fieldWeight in 701, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.03125 = fieldNorm(doc=701)
      0.33333334 = coord(1/3)
  0.33333334 = coord(1/3)

Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

0.020311687 = product of:
  0.06093506 = sum of:
    0.06093506 = product of:
      0.18280518 = sum of:
        0.18280518 = weight(_text_:3a in 5820) [ClassicSimilarity], result of:
          0.18280518 = score(doc=5820,freq=2.0), product of:
            0.4878985 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.057548698 = queryNorm
            0.3746787 = fieldWeight in 5820, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.03125 = fieldNorm(doc=5820)
      0.33333334 = coord(1/3)
  0.33333334 = coord(1/3)

Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.