Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 23. Dezember 2017)
1Drewer, P. ; Massion, F ; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun?.
In: https://archive-ouverte.unige.ch/unige:100073/. Deutsches Institut für Terminologie : O.O., 2017. 28 S.
Abstract: Diese Publikation beschreibt die Zusammenhänge zwischen wissenshaltigen begriffsorientierten Terminologien, Ontologien, Big Data und künstliche Intelligenz.
2Borchers, D.: Missing Link : Wenn der Kasten denkt - Niklas Luhmann und die Folgen.]17.12.2017].
Abstract: Gerade haben die Soziologen den 90. Geburstag des Systemtheoretikers Niklas Luhmann gefeiert. Die Informatiker stecken mitten in einem anspruchsvollen Digitalisierungsprojekt, seinen Gedankenkasten, sein "hölzernes Privat-Internet", zu verdaten.
3Madalli, D.P. ; Chatterjee, U. ; Dutta, B.: ¬An analytical approach to building a core ontology for food.
In: Journal of documentation. 73(2017) no.1, S.123-144.
Abstract: Purpose The purpose of this paper is to demonstrate the construction of a core ontology for food. To construct the core ontology, the authors propose here an approach called, yet another methodology for ontology plus (YAMO+). The goal is to exhibit the construction of a core ontology for a domain, which can be further extended and converted into application ontologies. Design/methodology/approach To motivate the construction of the core ontology for food, the authors have first articulated a set of application scenarios. The idea is that the constructed core ontology can be used to build application-specific ontologies for those scenarios. As part of the developmental approach to core ontology, the authors have proposed a methodology called YAMO+. It is designed following the theory of analytico-synthetic classification. YAMO+ is generic in nature and can be applied to build core ontologies for any domain. Findings Construction of a core ontology needs a thorough understanding of the domain and domain requirements. There are various challenges involved in constructing a core ontology as discussed in this paper. The proposed approach has proven to be sturdy enough to face the challenges that the construction of a core ontology poses. It is observed that core ontology is amenable to conversion to an application ontology. Practical implications The constructed core ontology for domain food can be readily used for developing application ontologies related to food. The proposed methodology YAMO+ can be applied to build core ontologies for any domain. Originality/value As per the knowledge, the proposed approach is the first attempt based on the study of the state of the art literature, in terms of, a formal approach to the design of a core ontology. Also, the constructed core ontology for food is the first one as there is no such ontology available on the web for domain food.
Inhalt: Vgl.: http://dx.doi.org/10.1108/JD-02-2016-0015.
4Wen, B. ; Horlings, E. ; Zouwen, M. van der ; Besselaar, P. van den: Mapping science through bibliometric triangulation : an experimental approach applied to water research.
In: Journal of the Association for Information Science and Technology. 68(2017) no.3, S.724-738.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23696/full.
Themenfeld: Wissensrepräsentation ; Visualisierung
5Zhitomirsky-Geffet, M. ; Erez, E.S. ; Bar-Ilan, J.: Toward multiviewpoint ontology construction by collaboration of non-experts and crowdsourcing : the case of the effect of diet on health.
In: Journal of the Association for Information Science and Technology. 68(2017) no.3, S.681-694.
Abstract: Domain experts are skilled in buliding a narrow ontology that reflects their subfield of expertise based on their work experience and personal beliefs. We call this type of ontology a single-viewpoint ontology. There can be a variety of such single viewpoint ontologies that represent a wide spectrum of subfields and expert opinions on the domain. However, to have a complete formal vocabulary for the domain they need to be linked and unified into a multiviewpoint model while having the subjective viewpoint statements marked and distinguished from the objectively true statements. In this study, we propose and implement a two-phase methodology for multiviewpoint ontology construction by nonexpert users. The proposed methodology was implemented for the domain of the effect of diet on health. A large-scale crowdsourcing experiment was conducted with about 750 ontological statements to determine whether each of these statements is objectively true, viewpoint, or erroneous. Typically, in crowdsourcing experiments the workers are asked for their personal opinions on the given subject. However, in our case their ability to objectively assess others' opinions was examined as well. Our results show substantially higher accuracy in classification for the objective assessment approach compared to the results based on personal opinions.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23686/full.
6Mestrovic, A. ; Cali, A.: ¬An ontology-based approach to information retrieval.
In: Semantic keyword-based search on structured data sources: COST Action IC1302. Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8-9, 2016, Revised Selected Papers. Eds.: A. Calì, A. et al. Springer International Publishing, 2017. S.150-156.
(Information Systems and Applications, incl. Internet/Web, and HCI; 10151)
Abstract: We define a general framework for ontology-based information retrieval (IR). In our approach, document and query expansion rely on a base taxonomy that is extracted from a lexical database or a Linked Data set (e.g. WordNet, Wiktionary etc.). Each term from a document or query is modelled as a vector of base concepts from the base taxonomy. We define a set of mapping functions which map multiple ontological layers (dimensions) onto the base taxonomy. This way, each concept from the included ontologies can also be represented as a vector of base concepts from the base taxonomy. We propose a general weighting schema which is used for the vector space model. Our framework can therefore take into account various lexical and semantic relations between terms and concepts (e.g. synonymy, hierarchy, meronymy, antonymy, geo-proximity, etc.). This allows us to avoid certain vocabulary problems (e.g. synonymy, polysemy) as well as to reduce the vector size in the IR tasks.
Inhalt: Vgl.: https://www.springerprofessional.de/an-ontology-based-approach-to-information-retrieval/12066802. Vgl. auch: http://www.keystone-cost.eu/ikc2016/program.php.
7Tang, X.-B. ; Wei Wei, G,-C.L. ; Zhu, J.: ¬An inference model of medical insurance fraud detection : based on ontology and SWRL.
In: Knowledge organization. 44(2017) no.2, S.84-96.
Abstract: Medical insurance fraud is common in many countries' medical insurance systems and represents a serious threat to the insurance funds and the benefits of patients. In this paper, we present an inference model of medical insurance fraud detection, based on a medical detection domain ontology that incorporates the knowledge base provided by the Medical Terminology, NKIMed, and Chinese Library Classification systems. Through analyzing the behaviors of irregular and fraudulent medical services, we defined the scope of the medical domain ontology relevant to the task and built the ontology about medical sciences and medical service behaviors. The ontology then utilizes Semantic Web Rule Language (SWRL) and Java Expert System Shell (JESS) to detect medical irregularities and mine implicit knowledge. The system can be used to improve the management of medical insurance risks.
8Finke, M. ; Risch, J.: "Match Me If You Can" : Sammeln und semantisches Aufbereiten von Fußballdaten.
In: Info7. 2017, Nr.2, S.37-43.
Abstract: Interviews, Spielstatistiken oder Videoaufzeichnungen sind für Fußballfans zwar zahlreich im Internet verfügbar, aber auf viele verschiedene Websites verstreut. "Semantic Media Mining" verknüpft nun Fußballdaten aus unterschiedlichen Quellen, bereitet sie semantisch auf und führt sie auf einer einzigen Website zusammen. Dadurch dokumentieren und visualisieren wir mehr als 50 Jahre Fußballgeschichte mit über 500 Mannschaften und 40.000 Spielern der Champions League, sowie der 1. und 2. Bundesliga.
Inhalt: Gewinnerbeitrag des Marianne-Englert-Preises 2017.
Anmerkung: Vgl.: www.info7.de/info7_2017-2_S-36-51.pdf.
Themenfeld: Wissensrepräsentation ; Semantic Web
9Ma, N. ; Zheng, H.T. ; Xiao, X.: ¬An ontology-based latent semantic indexing approach using long short-term memory networks.
In: Web and Big Data: First International Joint Conference, APWeb-WAIM 2017, Beijing, China, July 7-9, 2017, Proceedings, Part I. Eds.: L. Chen et al. Cham : Springer, 2017. S.185-199.
(Lecture notes in computer science; vol.10366)
Abstract: Nowadays, online data shows an astonishing increase and the issue of semantic indexing remains an open question. Ontologies and knowledge bases have been widely used to optimize performance. However, researchers are placing increased emphasis on internal relations of ontologies but neglect latent semantic relations between ontologies and documents. They generally annotate instances mentioned in documents, which are related to concepts in ontologies. In this paper, we propose an Ontology-based Latent Semantic Indexing approach utilizing Long Short-Term Memory networks (LSTM-OLSI). We utilize an importance-aware topic model to extract document-level semantic features and leverage ontologies to extract word-level contextual features. Then we encode the above two levels of features and match their embedding vectors utilizing LSTM networks. Finally, the experimental results reveal that LSTM-OLSI outperforms existing techniques and demonstrates deep comprehension of instances and articles.
Inhalt: Vgl.: https://link.springer.com/chapter/10.1007/978-3-319-63579-8_15. DOI: https://doi.org/10.1007/978-3-319-63579-8_15.
Themenfeld: Wissensrepräsentation ; Semantisches Umfeld in Indexierung u. Retrieval ; Automatisches Indexieren
Objekt: Latent Semantic Indexing
10Xu, G. ; Cao, Y. ; Ren, Y. ; Li, X. ; Feng, Z.: Network security situation awareness based on semantic ontology and user-defined rules for Internet of Things.
Abstract: Internet of Things (IoT) brings the third development wave of the global information industry which makes users, network and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response and predicting the development trend of IoT security, a new paradigm called network security situation awareness (NSSA) is proposed. However, it is limited by its ability to mine and evaluate security situation elements from multi-source heterogeneous network security information. To solve this problem, this paper proposes an IoT network security situation awareness model using situation reasoning method based on semantic ontology and user-defined rules. Ontology technology can provide a unified and formalized description to solve the problem of semantic heterogeneity in the IoT security domain. In this paper, four key sub-domains are proposed to reflect an IoT security situation: context, attack, vulnerability and network flow. Further, user-defined rules can compensate for the limited description ability of ontology, and hence can enhance the reasoning ability of our proposed ontology model. The examples in real IoT scenarios show that the ability of the network security situation awareness that adopts our situation reasoning method is more comprehensive and more powerful reasoning abilities than the traditional NSSA methods. [http://ieeexplore.ieee.org/abstract/document/7999187/]
Inhalt: DOI 10.1109/ACCESS.2017.2734681.
11Almeida Campos, M.L. de ; Espanha Gomes, H.: Ontology : several theories on the representation of knowledge domains.
In: Knowledge organization. 44(2017) no.3, S.178-186.
Abstract: Ontologies may be considered knowledge organization systems since the elements interact in a consistent conceptual structure. Theories of the representation of knowledge domains produce models that include definition, representation units, and semantic relationships that are essential for structuring such domain models. A realist viewpoint is proposed to enhance domain ontologies, as definitions provide structure that reveals not only ontological commitment but also relationships between unit representations.
Inhalt: Beitrag in einem Special Issue "New Trends for Knowledge Organization, Guest Editor: Renato Rocha Souza".
12Ejei, F. ; Beheshti, M.S.H. ; Rajabi, T. ; Ejehi, Z.: Enriching semantic relations of basic sciences ontology.
In: Knowledge organization. 44(2017) no.5, S.318-325.
Abstract: Ontology is the tool for representing knowledge in the fields of knowledge organization and artificial intelligence, and in the past decade, has gained attention in the semantic web as well. The main necessity in developing an ontology is generating a hierarchical structure of the concepts and the next requirement is creating and determining the type of the semantic relations among concepts. The present article introduces a semi-automated method for enriching semantic relations in the basic sciences ontology, which was developed based on domain-specific thesauri. In the proposed method, first the hierarchical relations in the ontology are reviewed and refined in order to distinguish their different types. In the next step, the concepts in the ontology are classified and the semantic relations among the concepts, based on the associative relationships in the thesaurus and semantic relation patterns extracted from a top-level ontology, are distinguished and added to the ontology. Using this method, semantic relations in the area of chemistry in the basic sciences ontology were refined and enriched. Almost seventy percent of the associative relationships were directly converted to semantic relations in the ontology. The remaining thirty percent are the inter-concept relations that can be concluded from other relations if the other associative relationships are correctly converted to semantic relations.
13Barcellos Almeida, M. ; Farinelli, F.: Ontologies for the representation of electronic medical records : the obstetric and neonatal ontology.
In: Journal of the Association for Information Science and Technology. 68(2017) no.11, S.2529-2542.
Abstract: Ontology is an interdisciplinary field that involves both the use of philosophical principles and the development of computational artifacts. As artifacts, ontologies can have diverse applications in knowledge management, information retrieval, and information systems, to mention a few. They have been largely applied to organize information in complex fields like Biomedicine. In this article, we present the OntoNeo Ontology, an initiative to build a formal ontology in the obstetrics and neonatal domain. OntoNeo is a resource that has been designed to serve as a comprehensive infrastructure providing scientific research and healthcare professionals with access to relevant information. The goal of OntoNeo is twofold: (a) to organize specialized medical knowledge, and (b) to provide a potential consensual representation of the medical information found in electronic health records and medical information systems. To describe our initiative, we first provide background information about distinct theories underlying ontology, top-level computational ontologies and their applications in Biomedicine. Then, we present the methodology employed in the development of OntoNeo and the results obtained to date. Finally, we discuss the applicability of OntoNeo by presenting a proof of concept that illustrates its potential usefulness in the realm of healthcare information systems.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23900/full.
Anmerkung: Beitrag in einem Special issue on biomedical information retrieval.
Wissenschaftsfach: Biochemie ; Medizin
14Ianni, G. et al. (Hrsg.): Reasoning Web : Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures.
Cham : Springer International Publishing, 2017. XI, 347 S.
(Lecture Notes in Computer Scienc;10370 )(Information Systems and Applications, incl. Internet/Web, and HCI)
Abstract: This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.
Inhalt: Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining
Themenfeld: Wissensrepräsentation ; Semantic Web ; Semantische Interoperabilität
LCSH: Computer science ; Mathematical logic ; Database management ; Information storage and retrieval ; Artificial intelligence ; Computer Science ; Mathematical Logic and Formal Languages
/ Terminologische Logik; Terminologische Logik ; OWL ; Ontologie / Semantic Web
RVK: SS 4800
15Rousset, M.-C. ; Atencia, M. ; David, J. ; Jouanot, F. ; Ulliana, F. ; Palombi, O.: Datalog revisited for reasoning in linked data.
In: Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al. Cham : Springer International Publishing, 2017. S.121-166.
(Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI)
Abstract: Linked Data provides access to huge, continuously growing amounts of open data and ontologies in RDF format that describe entities, links and properties on those entities. Equipping Linked Data with inference paves the way to make the Semantic Web a reality. In this survey, we describe a unifying framework for RDF ontologies and databases that we call deductive RDF triplestores. It consists in equipping RDF triplestores with Datalog inference rules. This rule language allows to capture in a uniform manner OWL constraints that are useful in practice, such as property transitivity or symmetry, but also domain-specific rules with practical relevance for users in many domains of interest. The expressivity and the genericity of this framework is illustrated for modeling Linked Data applications and for developing inference algorithms. In particular, we show how it allows to model the problem of data linkage in Linked Data as a reasoning problem on possibly decentralized data. We also explain how it makes possible to efficiently extract expressive modules from Semantic Web ontologies and databases with formal guarantees, whilst effectively controlling their succinctness. Experiments conducted on real-world datasets have demonstrated the feasibility of this approach and its usefulness in practice for data integration and information extraction.
Themenfeld: Semantic Web ; Wissensrepräsentation
Objekt: RDF ; OWL
16Lukasiewicz, T.: Uncertainty reasoning for the Semantic Web.
In: Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al. Cham : Springer International Publishing, 2017. S.276-291.
(Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI)
Abstract: The Semantic Web has attracted much attention, both from academia and industry. An important role in research towards the Semantic Web is played by formalisms and technologies for handling uncertainty and/or vagueness. In this paper, I first provide some motivating examples for handling uncertainty and/or vagueness in the Semantic Web. I then give an overview of some own formalisms for handling uncertainty and/or vagueness in the Semantic Web.
Themenfeld: Semantic Web ; Wissensrepräsentation
17Branch, F. ; Arias, T. ; Kennah, J. ; Phillips, R. ; Windleharth, T. ; Lee, J.H.: Representing transmedia fictional worlds through ontology.
In: Journal of the Association for Information Science and Technology. 68(2017) no.12, S.2771-2782.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23886/full.
Themenfeld: Multimedia ; Wissensrepräsentation
18Bauckhage, C.: Moderne Textanalyse : neues Wissen für intelligente Lösungen.
Abstract: Im Zuge der immer größeren Verfügbarkeit von Daten (Big Data) und rasanter Fortschritte im Daten-basierten maschinellen Lernen haben wir in den letzten Jahren Durchbrüche in der künstlichen Intelligenz erlebt. Dieser Vortrag beleuchtet diese Entwicklungen insbesondere im Hinblick auf die automatische Analyse von Textdaten. Anhand einfacher Beispiele illustrieren wir, wie moderne Textanalyse abläuft und zeigen wiederum anhand von Beispielen, welche praktischen Anwendungsmöglichkeiten sich heutzutage in Branchen wie dem Verlagswesen, der Finanzindustrie oder dem Consulting ergeben.
Inhalt: Folien der Präsentation anlässlich des GENIOS Datenbankfrühstücks 2016, 19. Oktober 2016.
Themenfeld: Wissensrepräsentation ; Data Mining
19Kiren, T. ; Shoaib, M.: ¬A novel ontology matching approach using key concepts.
In: Aslib journal of information management. 68(2016) no.1, S.99-111.
Abstract: Purpose Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched. Design/methodology/approach Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson's correlation coefficient and IR measures precision, recall and F-measure. Findings Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed. Originality/value On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.
Inhalt: Vgl.: http://dx.doi.org/10.1108/AJIM-04-2015-0054.
20Conde, A. ; Larrañaga, M. ; Arruarte, A. ; Elorriaga, J.A. ; Roth, D.: litewi: a combined term extraction and entity linking method for eliciting educational ontologies from textbooks.
In: Journal of the Association for Information Science and Technology. 67(2016) no.2, S.380-399.
Abstract: Major efforts have been conducted on ontology learning, that is, semiautomatic processes for the construction of domain ontologies from diverse sources of information. In the past few years, a research trend has focused on the construction of educational ontologies, that is, ontologies to be used for educational purposes. The identification of the terminology is crucial to build ontologies. Term extraction techniques allow the identification of the domain-related terms from electronic resources. This paper presents LiTeWi, a novel method that combines current unsupervised term extraction approaches for creating educational ontologies for technology supported learning systems from electronic textbooks. LiTeWi uses Wikipedia as an additional information source. Wikipedia contains more than 30 million articles covering the terminology of nearly every domain in 288 languages, which makes it an appropriate generic corpus for term extraction. Furthermore, given that its content is available in several languages, it promotes both domain and language independence. LiTeWi is aimed at being used by teachers, who usually develop their didactic material from textbooks. To evaluate its performance, LiTeWi was tuned up using a textbook on object oriented programming and then tested with two textbooks of different domains-astronomy and molecular biology.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23398/abstract.