Search (14 results, page 1 of 1)

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Abstract

This paper discusses and illustrates through examples how meaningful or deep learning can be supported through well-structured presentation of material, through giving learners schemas they can use to organize knowledge in their minds, and through helping learners to understand knowledge organization principles they can use to construct their own schemas. It is a call to all authors, educators and information designers to pay attention to meaningful presentation that expresses the internal structure of the domain and facilitates the learner's assimilation of concepts and their relationships.

Pages

S.22-32

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

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Abstract

To make better use of knowledge organization systems (KOS) for query expansion, we have developed a pattern-based technique for composition ontology mapping in a specific domain. The technique was tested in a two-step mapping. The user's free-text queries were first mapped to Getty's Art & Architecture Thesaurus (AAT) terms. The AAT-based queries were then mapped to a search engine's indexing vocabulary (ARTstor terms). The result indicated that our technique has improved the mapping success rate from 40% to 70%. We discuss also how the technique may be applied to other KOS mapping and how it may be implemented in practical systems.

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

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Abstract

This review introduces a comprehensive model of the cognitive process and mechanisms of individual sensemaking to provide a theoretical basis for: - empirical studies that improve our understanding of the cognitive process and mechanisms of sensemaking and integration of results of such studies; - education in critical thinking and sensemaking skills; - the design of sensemaking assistant tools that support and guide users. The paper reviews and extends existing sensemaking models with ideas from learning and cognition. It reviews literature on sensemaking models in human-computer interaction (HCI), cognitive system engineering, organizational communication, and library and information sciences (LIS), learning theories, cognitive psychology, and task-based information seeking. The model resulting from this synthesis moves to a stronger basis for explaining sensemaking behaviors and conceptual changes. The model illustrates the iterative processes of sensemaking, extends existing models that focus on activities by integrating cognitive mechanisms and the creation of instantiated structure elements of knowledge, and different types of conceptual change to show a complete picture of the cognitive processes of sensemaking. The processes and cognitive mechanisms identified provide better foundations for knowledge creation, organization, and sharing practices and a stronger basis for design of sensemaking assistant systems and tools.

Date

22. 8.2014 16:55:39

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Date

17. 1.2019 19:04:22

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Abstract

This article presents a logical analysis of the characteristics of indexing and their effects on retrieval performance.It establishes the ability to ask the questions one needs to ask as the foundation of performance evaluation, and recall and discrimination as the basic quantitative performance measures for binary noninteractive retrieval systems. It then defines the characteristics of indexing that affect retrieval - namely, indexing devices, viewpoint-based and importance-based indexing exhaustivity, indexing specifity, indexing correctness, and indexing consistency - and examines in detail their effects on retrieval. It concludes that retrieval performance depends chiefly on the match between indexing and the requirements of the individual query and on the adaption of the query formulation to the characteristics of the retrieval system, and that the ensuing complexity must be considered in the design and testing of retrieval systems

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Date

22. 7.2006 18:04:19

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Abstract

This study demonstrates an improved conceptual foundation to support well-structured analysis of image topicality. First we present a conceptual framework for analyzing image topicality, explicating the layers, the perspectives, and the topical relevance relationships involved in modeling the topicality of art images. We adapt a generic relevance typology to image analysis by extending it with definitions and relationships specific to the visual art domain and integrating it with schemes of image-text relationships that are important for image subject indexing. We then apply the adapted typology to analyze the topical relevance relationships between 11 art images and 768 image tags assigned by art historians and librarians. The original contribution of our work is the topical structure analysis of image tags that allows the viewer to more easily grasp the content, context, and meaning of an image and quickly tune into aspects of interest; it could also guide both the indexer and the searcher to specify image tags/descriptors in a more systematic and precise manner and thus improve the match between the two parties. An additional contribution is systematically examining and integrating the variety of image-text relationships from a relevance perspective. The paper concludes with implications for relational indexing and social tagging.

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Abstract

Critical comments on the BSO concern basic principles used in system construction, the quality of which, from the standpoint of the author, does not meet the requirements set out for the BSO. First of all, it would be necessary to revise and clearly formulate the purpose of the system, to make and consistently implement a basic decision on its structural characteristics, to provide for high-quality conceptual analysis and subject expertise which directly influence the content of the tables, and to clearly display supplemetary materials for the tables

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Date

27.11.2015 20:52:22

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Abstract

This chapter describes not so much what digital libraries are but what digital libraries with semantic support could and should be. It discusses the nature of Knowledge Organization Systems (KOS) and how KOS can support digital library users. It projects a vision for designers to make and for users to demand better digital libraries. What is a digital library? The term \Digital Library" (DL) is used to refer to a range of systems, from digital object and metadata repositories, reference-linking systems, archives, and content management systems to complex systems that integrate advanced digital library services and support for research and practice communities. A DL may offer many technology-enabled functions and services that support users, both as information producers and as information users. Many of these functions appear in information systems that would not normally be considered digital libraries, making boundaries even more blurry. Instead of pursuing the hopeless quest of coming up with the definition of digital library, we present a framework that allows a clear and somewhat standardized description of any information system so that users can select the system(s) that best meet their requirements. Section 2 gives a broad outline for more detail see the DELOS DL Reference Model.

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Abstract

This article proposes an approach to mapping between Knowledge Organization Systems (KOS), including ontologies, classifications, taxonomies, and thesauri and even natural languages, that is based on deep semantics. In this approach, concepts in each KOS are expressed through canonical expressions, such as description logic formulas, that combine atomic (or elemental) concepts drawn from a core classification. Relationships between concepts within or across KOS can then be derived by reasoning over the canonical expressions. The canonical expressions can also be used to provide a facet-based query formulation front-end for free-text search. The article illustrates this approach through many examples. It presents methods for the efficient construction of canonical expressions (linguistic analysis, exploiting information in the KOS and their hierarchies, and crowdsourcing) that make this approach feasible.

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Abstract

As an attempt to make a general structural theory of information retrieval, a documentation system (DS) is defined as a formal system consisting of (a) a set o of objects (documents); (b) a set A++ of elementary attributes (key-words), from which further attributes may be constructed: A++ generates A; (c) a set of axioms of the form X++(x)=m (m¯M, M a set of constant connecting attributes with objects: from the axioms further theorems (=true statements) may be constructed. By use of the theorems, different mappings O -> P(o) (P(o) set of all subsets of o) (search question -> set of documents retrieved) are defined. The type of a DS depends on two basic decisions: (1) choice of the rules for the construction of attributes and theorems, e.g., logical product in coordinate indexing; links. (2) choice of M; M may consist of the two constants 'applicable' and 'not applicable', or some positive integers, ...; Further practical decisions: A++ hierarchical or not; kind of mapping; introduction of roles (=further attributes). The most simple case - ordinary two-valued Coordinate Indexing - is discusssed in detail; o is a free distributive (but not Boolean) lattice, the homographic image a ring of subsets of o; instead of negation which is not useful, a useful retrieval operation 'praeternagation' is introduced. Furthermore these are discussed: a generalized definition of superimposed coding, some functions for the distance of objects or attributes; optimization and automatic derivation of classifications. The model takes into account term-term relations and document-document relations. It may serve as a structural framework in terms of which the functional problems of retrieval theory may be expressed more clearly

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Abstract

This article proposes a model of document selection by real users of a bibliographic retrieval system. It reports on Part 1 of a longitudinal study of decision making on document use by academics during a actual research project. (Part 2 followed up the same users on how the selected documents were actually used in subsequent stages). The participants are 25 self-selected faculty and graduate students in Agricultural Economics. After a reference interview, the researcher conducted a search of DIALOG databases and prepared a printout. The users selected documents from this printout, They were asked to read and think aloud while selecting documents. There verbal reports were recorded and analyzed from a utiliy-theoretic perspective. The following model of the decision-making in the selection process emerged: document information lemenets (DIEs) in document records provide the information for judging the documents on 11 criteria (including topicality, orientation, quality, novelty, and authority); the criteria judgments are comninded in an assessment of document value along 5 dimensions (Epistemic, functional, conditional, social, and emotional values), leading to the use decision. This model accounts for the use of personal knowledge and decision strategies applied in the selection process. The model has implications for the design of an intelligent document selection assistant

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Abstract

Synthesizing and building on many ideas from the literature, this article presents an improved conceptual framework that clarifies the notion of relevance with its many elements, variables, criteria, and situational factors. Relevance is defined as a Relationship (R) between an Information Object (I) and an Information Need (N) (which consists of Topic, User, Problem/Task, and Situation/Context) with focus on R. This defines Relevance-as-is (conceptual relevance, strong relevance). To determine relevance, an Agent A (a person or system) operates on a representation I? of the information object and a representation N? of the information need, resulting in relevance-as-determined (operational measure of relevance, weak relevance, an approximation). Retrieval tests compare relevance-as-determined by different agents. This article discusses and compares two major approaches to conceptualizing relevance: the entity-focused approach (focus on elaborating the entities involved in relevance) and the relationship-focused approach (focus on explicating the relational nature of relevance). The article argues that because relevance is fundamentally a relational construct the relationship-focused approach deserves a higher priority and more attention than it has received. The article further elaborates on the elements of the framework with a focus on clarifying several critical issues on the discourse on relevance.