Search (74 results, page 2 of 4)

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Abstract

This paper proposes an analysis of faceted theory and of various knowledge organization approaches. Building upon the faceted theory of S.R. Ranganathan (1967), the paper intends to address the faceted classification approach applied to build domain ontologies. Based on this perspective, an ontology of a music domain has been analyzed that would serve as a case study. As classificatory ontologies are employed to represent the relationships of entities and objects on the web, the faceted approach is deemed as an effective means to help organize web content. While different knowledge organization systems are being employed to address the cluttered Web in different contexts and with various degrees of effectiveness, faceted ontologies have an enormous potential for addressing this issue by performing.

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Abstract

Mathematical modelling is a field of applied mathematics with applications in other disciplines. The availability of a formal ontology and derived benefits, such as the possibility of conducting automated reasoning about the ontological classes of the domains, greatly reduce the barrier of entry in the field for non-experts, while helping the establishment of a more precise and controlled vocabulary among the domain experts involved in mathematical modelling. This work focuses on Mathematical Models applied to the natural sciences and as a case study the field of mathematical epidemiology has been chosen for this ontology. We propose the development of an ontology of mathematical models which is general enough and not restricted in its applicability, yet is developed considering the specific needs of a particular application domain.

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Series

Studies in health technology and informatics; 165

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Abstract

The field of knowledge organization (KO) can be described as composed of the four distinct but connected layers of theory, systems, representation, and application. This paper focuses on the relations between KO theory and KO systems. It is acknowledged how the structure of KO systems is the product of a mixture of ontological, epistemological, and pragmatical factors. However, different systems give different priorities to each factor. A more ontologically-oriented approach, though not offering quick solutions for any particular group of users, will produce systems of wide and long-lasting application as they are based on general, shareable principles. I take the case of the ontological theory of integrative levels, which has been considered as a useful source for general classifications for several decades, and is currently implemented in the Integrative Levels Classification system. The theory produces a sequence of main classes modelling a natural order between phenomena. This order has interesting effects also on other features of the system, like the citation order of concepts within compounds. As it has been shown by facet analytical theory, it is useful that citation order follow a principle of inversion, as compared to the order of the same concepts in the schedules. In the light of integrative levels theory, this principle also acquires an ontological meaning: phenomena of lower level should be cited first, as most often they act as specifications of higher-level ones. This ontological principle should be complemented by consideration of the epistemological treatment of phenomena: in case a lower-level phenomenon is the main theme, it can be promoted to the leading position in the compound subject heading. The integration of these principles is believed to produce optimal results in the ordering of knowledge contents.

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Abstract

Research in ontology has in recent years become widespread in the field of information systems, in distinct areas of sciences, in business, in economy, and in industry. The importance of ontologies is increasingly recognized in fields diverse as in e-commerce, semantic web, enterprise, information integration, qualitative modelling of physical systems, natural language processing, knowledge engineering, and databases. Ontologies provide formal specifications and harmonized definitions of concepts used to represent knowledge of specific domains. An ontology supplies a unifying framework for communication and establishes the basis of the knowledge about a specific domain. The term ontology has two meanings, it denotes, on the one hand, a research area, on the other hand, a system of organized knowledge. A system of knowledge may exhibit various degrees of formality; in the strongest sense it is an axiomatized and formally represented theory. which is denoted throughout this paper by the term axiomatized ontology. We use the term formal ontology to name an area of research which is becoming a science similar as formal or mathematical logic. Formal ontology is an evolving science which is concerned with the systematic development of axiomatic theories describing forms, modes, and views of being of the world at different levels of abstraction and granularity. Formal ontology combines the methods of mathematical logic with principles of philosophy, but also with the methods of artificial intelligence and linguistics. At themost general level of abstraction, formal ontology is concerned with those categories that apply to every area of the world. The application of formal ontology to domains at different levels of generality yields knowledge systems which are called, according to the level of abstraction, Top Level Ontologies or Foundational Ontologies, Core Domain or Domain Ontologies. Top level or foundational ontologies apply to every area of the world, in contrast to the various Generic, Domain Core or Domain Ontologies, which are associated to more restricted fields of interest. A foundational ontology can serve as a unifying framework for representation and integration of knowledge and may support the communication and harmonisation of conceptual systems. The current paper presents an overview about the current stage of the foundational ontology GFO.

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Abstract

Freely faceted classifications allow for free combination of concepts across all knowledge domains, and for sorting of the resulting compound classmarks. Starting from work by the Classification Research Group, the Integrative Levels Classification (ILC) project has produced a first edition of a general freely faceted scheme. The system is managed as a MySQL database, and can be browsed through a Web interface. The ILC database structure provides a case for identifying and representing the structural elements of any freely faceted classification. These belong to both the notational and the verbal planes. Notational elements include: arrays, chains, deictics, facets, foci, place of definition of foci, examples of combinations, subclasses of a faceted class, groupings, related classes; verbal elements include: main caption, synonyms, descriptions, included terms, related terms, notes. Encoding of some of these elements in an international mark-up format like SKOS can be problematic, especially as this does not provide for faceted structures, although approximate SKOS equivalents are identified for most of them.

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Abstract

Improving Information retrieval by employing the use of ontologies to overcome the limitations of syntactic search has been one of the inspirations since its emergence. This paper proposes a conceptual framework to exploit ontology based Information retrieval. This framework constitutes of five phases namely Query parsing, word stemming, ontology matching, weight assignment, ranking and Information retrieval. In the first phase, the user query is parsed into sequence of words. The parsed contents are curtailed to identify the significant word by ignoring superfluous terms such as "to", "is","ed", "about" and the like in the stemming phase. The objective of the stemming phase is to throttle feature descriptors to root words, which in turn will increase efficiency; this reduces the time consumed for searching the superfluous terms, which may not significantly influence the effectiveness of the retrieval process. In the third phase ontology matching is carried out by matching the parsed words with the relevant terms in the existing ontology. If the ontology does not exist, it is recommended to generate the required ontology. In the fourth phase the weights are assigned based on the distance between the stemmed words and the terms in the ontology uses improved matchmaking algorithm. The range of weights varies from 0 to 1 based on the level of distance in the ontology (superclass-subclass). The aggregate weights are calculated for the all the combination of stemmed words. The combination with the highest score is ranked as the best and the corresponding information is retrieved. The conceptual workflow is illustrated with an e-governance case study Academic Information System.

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Abstract

In this paper, we focus on applying sentiment analysis to resources from online art collections, by exploiting, as information source, tags intended as textual traces that visitors leave to comment artworks on social platforms. We present a framework where methods and tools from a set of disciplines, ranging from Semantic and Social Web to Natural Language Processing, provide us the building blocks for creating a semantic social space to organize artworks according to an ontology of emotions. The ontology is inspired by the Plutchik's circumplex model, a well-founded psychological model of human emotions. Users can be involved in the creation of the emotional space, through a graphical interactive interface. The development of such semantic space enables new ways of accessing and exploring art collections. The affective categorization model and the emotion detection output are encoded into W3C ontology languages. This gives us the twofold advantage to enable tractable reasoning on detected emotions and related artworks, and to foster the interoperability and integration of tools developed in the Semantic Web and Linked Data community. The proposal has been evaluated against a real-word case study, a dataset of tagged multimedia artworks from the ArsMeteo Italian online collection, and validated through a user study.

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Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

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Abstract

The purpose of this research is to develop an ontology with subsequent testing and evaluation, for identifying utility and value. The domain that has been chosen is human nervous system (HNS) disorders. It is hypothesized here that an ontology-based patient records management system is more effective in meeting and addressing complex information needs of health-care personnel. Therefore, this study has been based on the premise that developing an ontology and using it as a component of the search interface in hospital records management systems will lead to more efficient and effective management of health-care.It is proposed here to develop an ontology of the domain of HNS disorders using a standard vocabulary such as MeSH or SNOMED CT. The principal classes of an ontology include facet analysis for arranging concepts based on their common characteristics to build mutually exclusive classes. We combine faceted theory with description logic, which helps us to better query and retrieve data by implementing an ontological model. Protégé 5.2.0 was used as ontology editor. The use of ontologies for domain modelling will be of acute help to doctors for searching patient records. In this paper we show how the faceted approach helps us to build a flexible model and retrieve better information. We use the medical domain as a case study to show examples and implementation.

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Abstract

Research on categories indicates that superordinate categories lack informativeness because they are represented by only a few attributes while subordinate categories lack cognitive economy because they are represented by too many attributes (e.g., Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976). Basic level categories balance informativeness and cognitive economy: They represent the most attributes common to category members and the fewest attributes shared across categories. Green (2006) has suggested that the universality of basic level categories can be used for building crosswalks between classificatory systems. However, studies of basic level categories in KO systems have assumed that the notion of a basic level category is understood and have failed to operationalize the notion of "basic level category" before applying it in the analysis of user-generated vocabularies. Heidegger's (1953/1996) notion of handiness (i.e., zuhandenheit, or being "at hand" can provide a framework for understanding the unstable and relational nature of basic level categories and for operationalizing basic level categories in KO research.

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Abstract

This paper provides an analysis of the knowledge structure underlying DBpedia, one of the largest and most heavily used datasets in the current Linked Data landscape. The study reveals an evolving knowledge representation environment where different descriptive and classification approaches are employed concurrently. This analysis opens up a new area of research to which the knowledge organization community can make a significant contribution.

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Source

Annals of library and information studies. 62(2015) no.4, S.274-280

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Footnote

Rez. in: Annals of Library and Information Studies 62(2015) no.4, S.299-300 (A.K. Das)

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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.

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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.

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