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  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.14
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
    Source
    Graph-Based Methods for Natural Language Processing - proceedings of the Thirteenth Workshop (TextGraphs-13): November 4, 2019, Hong Kong : EMNLP-IJCNLP 2019. Ed.: Dmitry Ustalov
  2. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.12
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
    LCSH
    Statistics / Graphic methods
    Science / Study and teaching / Graphic methods
    Subject
    Statistics / Graphic methods
    Science / Study and teaching / Graphic methods
  3. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.09
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    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    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.
  4. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.07
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    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.
  5. Curras, E.: Ontologies, taxonomy and thesauri in information organisation and retrieval (2010) 0.02
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    Abstract
    The originality of this book, which deals with such a new subject matter, lies in the application of methods and concepts never used before - such as Ontologies and Taxonomies, as well as Thesauri - to the ordering of knowledge based on primary information. Chapters in the book also examine the study of Ontologies, Taxonomies and Thesauri from the perspective of Systematics and General Systems Theory. "Ontologies, Taxonomy and Thesauri in Information Organisation and Retrieval" will be extremely useful to those operating within the network of related fields, which includes Documentation and Information Science.
    Content
    Inhalt: 1. From classifications to ontologies Knowledge - A new concept of knowledge - Knowledge and information - Knowledge organisation - Knowledge organisation and representation - Cognitive sciences - Talent management - Learning systematisation - Historical evolution - From classification to knowledge organisation - Why ontologies exist - Ontologies - The structure of ontologies 2. Taxonomies and thesauri From ordering to taxonomy - The origins of taxonomy - Hierarchical and horizontal order - Correlation with classifications - Taxonomy in computer science - Computing taxonomy - Definitions - Virtual taxonomy, cybernetic taxonomy - Taxonomy in Information Science - Similarities between taxonomies and thesauri - ifferences between taxonomies and thesauri 3. Thesauri Terminology in classification systems - Terminological languages - Thesauri - Thesauri definitions - Conditions that a thesaurus must fulfil - Historical evolution - Classes of thesauri 4. Thesauri in (cladist) systematics Systematics - Systematics as a noun - Definitions and historic evolution over time - Differences between taxonomy and systematics - Systematics in thesaurus construction theory - Classic, numerical and cladist systematics - Classic systematics in information science - Numerical systematics in information science - Thesauri in cladist systematics - Systematics in information technology - Some examples 5. Thesauri in systems theory Historical evolution - Approach to systems - Systems theory applied to the construction of thesauri - Components - Classes of system - Peculiarities of these systems - Working methods - Systems theory applied to ontologies and taxonomies
  6. Broughton, V.: Facet analysis as a fundamental theory for structuring subject organization tools (2007) 0.02
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    Abstract
    The presentation will examine the potential of facet analysis as a basis for determining status and relationships of concepts in subject based tools using a controlled vocabulary, and the extent to which it can be used as a general theory of knowledge organization as opposed to a methodology for structuring classifications only.
    Date
    26.12.2011 13:21:29
  7. Hodgson, J.P.E.: Knowledge representation and language in AI (1991) 0.02
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    Abstract
    The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.
    LCSH
    Knowledge / representation (Information theory)
    Subject
    Knowledge / representation (Information theory)
  8. Handbook on ontologies (2004) 0.02
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    Abstract
    An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind.
    LCSH
    Knowledge representation (Information theory)
    Conceptual structures (Information theory)
    Subject
    Knowledge representation (Information theory)
    Conceptual structures (Information theory)
  9. Quillian, M.R.: Word concepts : a theory and simulation of some basic semantic capabilities. (1967) 0.02
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    Abstract
    In order to discover design principles for a large memory that can enable it to serve as the base of knowledge underlying human-like language behavior, experiments with a model memory are being performed. This model is built up within a computer by "recoding" a body of information from an ordinary dictionary into a complex network of elements and associations interconnecting them. Then, the ability of a program to use the resulting model memory effectively for simulating human performance provides a test of its design. One simulation program, now running, is given the model memory and is required to compare and contrast the meanings of arbitrary pairs of English words. For each pair, the program locates any relevant semantic information within the model memory, draws inferences on the basis of this, and thereby discovers various relationships between the meanings of the two words. Finally, it creates English text to express its conclusions. The design principles embodied in the memory model, together with some of the methods used by the program, constitute a theory of how human memory for semantic and other conceptual material may be formatted, organized, and used.
  10. Teskey, F.N.: Enriched knowledge representation for information retrieval (1987) 0.02
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    Abstract
    In this paper we identify the need for a new theory of information. An information model is developed which distinguishes between data, as directly observable facts, information, as structured collections of data, and knowledge as methods of using information. The model is intended to support a wide range of information systems. In the paper we develop the use of the model for a semantic information retrieval system using the concept of semantic categories. The likely benefits of this area discussed, though as yet no detailed evaluation has been conducted.
  11. Gnoli, C.: Fundamentos ontológicos de la organización del conocimiento : la teoría de los niveles integrativos aplicada al orden de cita (2011) 0.02
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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.
    Footnote
    Übers. des Titels: Ontological foundations in knowledge organization: the theory of integrative levels applied in citation order.
    Source
    Scire. 17(2011) no.1, S.29-34
  12. Maculan, B.C.M. dos; Lima, G.A. de; Oliveira, E.D.: Conversion methods from thesaurus to ontologies : a review (2016) 0.02
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    Source
    Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
  13. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.02
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    Date
    23. 7.2017 13:49:22
    LCSH
    Knowledge representation (Information theory)
    Subject
    Knowledge representation (Information theory)
  14. Priss, U.: Faceted information representation (2000) 0.01
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    Abstract
    This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)
    Date
    22. 1.2016 17:47:06
  15. Madalli, D.P.; Balaji, B.P.; Sarangi, A.K.: Music domain analysis for building faceted ontological representation (2014) 0.01
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    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
  16. Herre, H.: Formal ontology and the foundation of knowledge organization (2013) 0.01
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    Abstract
    Research in ontology has, in recent years, become widespread in the field of information systems, in various 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, information science, qualitative modeling 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, it establishes a basis for knowledge organization and knowledge representation and contributes to theory formation and modeling of a specific domain. In the current paper, we present and discuss principles of organization and representation of knowledge that grew out of the use of formal ontology. The core of the discussed ontological framework is a top-level ontology, called GFO (General Formal Ontology), which is being developed at the University of Leipzig. These principles make use of the onto-axiomatic method, of graduated conceptualizations, of levels of reality, and of top-level-supported methods for ontology-development. We explore the interrelations between formal ontology and knowledge organization, and argue for a close interaction between both fields
    Footnote
    Part of a section "Papers from the 13th Meeting of the German ISKO "Theory, Information, and Organization of Knowledge," Potsdam, 19-20 March 2013"
  17. Nagao, M.: Knowledge and inference (1990) 0.01
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    Abstract
    Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.
    LCSH
    Knowledge, Theory of
    Subject
    Knowledge, Theory of
  18. Clark, M.; Kim, Y.; Kruschwitz, U.; Song, D.; Albakour, D.; Dignum, S.; Beresi, U.C.; Fasli, M.; Roeck, A De: Automatically structuring domain knowledge from text : an overview of current research (2012) 0.01
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    Abstract
    This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.
    Date
    29. 1.2016 18:29:51
  19. Poli, R.: Upper ontologies hold it together (2008) 0.01
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    Abstract
    After presenting some of the basic features of upper ontologies, the thesis is defended that all the relations needed by any concrete application can be generated by a small set of general relations, by adding proper ontological constraints to the general relations' arguments. This procedure provides an explicit and verifiable grounding to all forms of knowledge managements, including acquisition, interchange, integration, reuse, merging, aligning and updating knowledge. Upper ontologies therefore provide cues for developing both unification and decomposition methods. Finally, upper ontologies pave the ground for enhancing automatic reasoning and other machine-oriented procedures. I conclude by mentioning a difficulty in the theory of semantic fields.
  20. Atanassova, I.; Bertin, M.: Semantic facets for scientific information retrieval (2014) 0.01
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    Abstract
    We present an Information Retrieval System for scientific publications that provides the possibility to filter results according to semantic facets. We use sentence-level semantic annotations that identify specific semantic relations in texts, such as methods, definitions, hypotheses, that correspond to common information needs related to scientific literature. The semantic annotations are obtained using a rule-based method that identifies linguistic clues organized into a linguistic ontology. The system is implemented using Solr Search Server and offers efficient search and navigation in scientific papers.
    Source
    Semantic Web Evaluation Challenge. SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers. Eds.: V. Presutti et al

Authors

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  • e 174
  • d 20
  • f 1
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