Search (545 results, page 1 of 28)

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Abstract

Despite the dissemination of modeling languages and tools for representation and construction of ontologies, their underlying methodologies can still be improved. As a consequence, ontology tools can be enhanced accordingly, in order to support users through the ontology construction process. This paper proposes suggestions for ontology tools' improvement based on a case study within the domain of bioinformatics, applying a reuse method ology. Quantitative and qualitative analyses were carried out on a subset of 28 terms of Gene Ontology on a semi-automatic alignment with other biomedical ontologies. As a result, a report is presented containing suggestions for enhancing ontology reuse tools, which is a product derived from difficulties that we had in reusing a set of OBO ontologies. For the reuse process, a set of steps closely related to those of Pinto and Martin's methodology was used. In each step, it was observed that the experiment would have been significantly improved if ontology manipulation tools had provided certain features. Accordingly, problematic aspects in ontology tools are presented and suggestions are made aiming at getting better results in ontology reuse.

Date

22. 2.2013 12:03:53

Type

a

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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.

Date

23. 7.2017 13:49:22

Imprint

Berlin : De Gruyter Saur

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Abstract

Considering the characteristics of hypertext systems and problems such as cognitive overload and the disorientation of users, this project studies subject hypertext documents that have undergone conceptual structuring using facets for content representation and improvement of information retrieval during navigation. The main objective was to assess the possibility of the application of topic map technology for automating the compatibilization process of these structures. For this purpose, two dissertations from the UFMG Information Science Post-Graduation Program were adopted as samples. Both dissertations had been duly analyzed and structured on the MHTX (Hypertextual Map) prototype database. The faceted structures of both dissertations, which had been represented in conceptual maps, were then converted into topic maps. It was then possible to use the merge property of the topic maps to promote the semantic interrelationship between the maps and, consequently, between the hypertextual information resources proper. The merge results were then analyzed in the light of theories dealing with the compatibilization of languages developed within the realm of information technology and librarianship from the 1960s on. The main goals accomplished were: (a) the detailed conceptualization of the merge process of the topic maps, considering the possible compatibilization levels and the applicability of this technology in the integration of faceted structures; and (b) the production of a detailed sequence of steps that may be used in the implementation of topic maps based on faceted structures.

Date

22. 2.2013 11:39:23

Type

a

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Abstract

Depuis son apparition au début des années 90, le World Wide Web (WWW ou Web) a offert un accès universel aux connaissances et le monde de l'information a été principalement témoin d'une grande révolution (la révolution numérique). Il est devenu rapidement très populaire, ce qui a fait de lui la plus grande et vaste base de données et de connaissances existantes grâce à la quantité et la diversité des données qu'il contient. Cependant, l'augmentation et l'évolution considérables de ces données soulèvent d'importants problèmes pour les utilisateurs notamment pour l'accès aux documents les plus pertinents à leurs requêtes de recherche. Afin de faire face à cette explosion exponentielle du volume de données et faciliter leur accès par les utilisateurs, différents modèles sont proposés par les systèmes de recherche d'information (SRIs) pour la représentation et la recherche des documents web. Les SRIs traditionnels utilisent, pour indexer et récupérer ces documents, des mots-clés simples qui ne sont pas sémantiquement liés. Cela engendre des limites en termes de la pertinence et de la facilité d'exploration des résultats. Pour surmonter ces limites, les techniques existantes enrichissent les documents en intégrant des mots-clés externes provenant de différentes sources. Cependant, ces systèmes souffrent encore de limitations qui sont liées aux techniques d'exploitation de ces sources d'enrichissement. Lorsque les différentes sources sont utilisées de telle sorte qu'elles ne peuvent être distinguées par le système, cela limite la flexibilité des modèles d'exploration qui peuvent être appliqués aux résultats de recherche retournés par ce système. Les utilisateurs se sentent alors perdus devant ces résultats, et se retrouvent dans l'obligation de les filtrer manuellement pour sélectionner l'information pertinente. S'ils veulent aller plus loin, ils doivent reformuler et cibler encore plus leurs requêtes de recherche jusqu'à parvenir aux documents qui répondent le mieux à leurs attentes. De cette façon, même si les systèmes parviennent à retrouver davantage des résultats pertinents, leur présentation reste problématique. Afin de cibler la recherche à des besoins d'information plus spécifiques de l'utilisateur et améliorer la pertinence et l'exploration de ses résultats de recherche, les SRIs avancés adoptent différentes techniques de personnalisation de données qui supposent que la recherche actuelle d'un utilisateur est directement liée à son profil et/ou à ses expériences de navigation/recherche antérieures. Cependant, cette hypothèse ne tient pas dans tous les cas, les besoins de l'utilisateur évoluent au fil du temps et peuvent s'éloigner de ses intérêts antérieurs stockés dans son profil.
Dans d'autres cas, le profil de l'utilisateur peut être mal exploité pour extraire ou inférer ses nouveaux besoins en information. Ce problème est beaucoup plus accentué avec les requêtes ambigües. Lorsque plusieurs centres d'intérêt auxquels est liée une requête ambiguë sont identifiés dans le profil de l'utilisateur, le système se voit incapable de sélectionner les données pertinentes depuis ce profil pour répondre à la requête. Ceci a un impact direct sur la qualité des résultats fournis à cet utilisateur. Afin de remédier à quelques-unes de ces limitations, nous nous sommes intéressés dans ce cadre de cette thèse de recherche au développement de techniques destinées principalement à l'amélioration de la pertinence des résultats des SRIs actuels et à faciliter l'exploration de grandes collections de documents. Pour ce faire, nous proposons une solution basée sur un nouveau concept d'indexation et de recherche d'information appelé la projection multi-espaces. Cette proposition repose sur l'exploitation de différentes catégories d'information sémantiques et sociales qui permettent d'enrichir l'univers de représentation des documents et des requêtes de recherche en plusieurs dimensions d'interprétations. L'originalité de cette représentation est de pouvoir distinguer entre les différentes interprétations utilisées pour la description et la recherche des documents. Ceci donne une meilleure visibilité sur les résultats retournés et aide à apporter une meilleure flexibilité de recherche et d'exploration, en donnant à l'utilisateur la possibilité de naviguer une ou plusieurs vues de données qui l'intéressent le plus. En outre, les univers multidimensionnels de représentation proposés pour la description des documents et l'interprétation des requêtes de recherche aident à améliorer la pertinence des résultats de l'utilisateur en offrant une diversité de recherche/exploration qui aide à répondre à ses différents besoins et à ceux des autres différents utilisateurs. Cette étude exploite différents aspects liés à la recherche personnalisée et vise à résoudre les problèmes engendrés par l'évolution des besoins en information de l'utilisateur. Ainsi, lorsque le profil de cet utilisateur est utilisé par notre système, une technique est proposée et employée pour identifier les intérêts les plus représentatifs de ses besoins actuels dans son profil. Cette technique se base sur la combinaison de trois facteurs influents, notamment le facteur contextuel, fréquentiel et temporel des données. La capacité des utilisateurs à interagir, à échanger des idées et d'opinions, et à former des réseaux sociaux sur le Web, a amené les systèmes à s'intéresser aux types d'interactions de ces utilisateurs, au niveau d'interaction entre eux ainsi qu'à leurs rôles sociaux dans le système. Ces informations sociales sont abordées et intégrées dans ce travail de recherche. L'impact et la manière de leur intégration dans le processus de RI sont étudiés pour améliorer la pertinence des résultats.
Since its appearance in the early 90's, the World Wide Web (WWW or Web) has provided universal access to knowledge and the world of information has been primarily witness to a great revolution (the digital revolution). It quickly became very popular, making it the largest and most comprehensive database and knowledge base thanks to the amount and diversity of data it contains. However, the considerable increase and evolution of these data raises important problems for users, in particular for accessing the documents most relevant to their search queries. In order to cope with this exponential explosion of data volume and facilitate their access by users, various models are offered by information retrieval systems (IRS) for the representation and retrieval of web documents. Traditional SRIs use simple keywords that are not semantically linked to index and retrieve these documents. This creates limitations in terms of the relevance and ease of exploration of results. To overcome these limitations, existing techniques enrich documents by integrating external keywords from different sources. However, these systems still suffer from limitations that are related to the exploitation techniques of these sources of enrichment. When the different sources are used so that they cannot be distinguished by the system, this limits the flexibility of the exploration models that can be applied to the results returned by this system. Users then feel lost to these results, and find themselves forced to filter them manually to select the relevant information. If they want to go further, they must reformulate and target their search queries even more until they reach the documents that best meet their expectations. In this way, even if the systems manage to find more relevant results, their presentation remains problematic. In order to target research to more user-specific information needs and improve the relevance and exploration of its research findings, advanced SRIs adopt different data personalization techniques that assume that current research of user is directly related to his profile and / or previous browsing / search experiences.
However, this assumption does not hold in all cases, the needs of the user evolve over time and can move away from his previous interests stored in his profile. In other cases, the user's profile may be misused to extract or infer new information needs. This problem is much more accentuated with ambiguous queries. When multiple POIs linked to a search query are identified in the user's profile, the system is unable to select the relevant data from that profile to respond to that request. This has a direct impact on the quality of the results provided to this user. In order to overcome some of these limitations, in this research thesis, we have been interested in the development of techniques aimed mainly at improving the relevance of the results of current SRIs and facilitating the exploration of major collections of documents. To do this, we propose a solution based on a new concept and model of indexing and information retrieval called multi-spaces projection. This proposal is based on the exploitation of different categories of semantic and social information that enrich the universe of document representation and search queries in several dimensions of interpretations. The originality of this representation is to be able to distinguish between the different interpretations used for the description and the search for documents. This gives a better visibility on the results returned and helps to provide a greater flexibility of search and exploration, giving the user the ability to navigate one or more views of data that interest him the most. In addition, the proposed multidimensional representation universes for document description and search query interpretation help to improve the relevance of the user's results by providing a diversity of research / exploration that helps meet his diverse needs and those of other different users. This study exploits different aspects that are related to the personalized search and aims to solve the problems caused by the evolution of the information needs of the user. Thus, when the profile of this user is used by our system, a technique is proposed and used to identify the interests most representative of his current needs in his profile. This technique is based on the combination of three influential factors, including the contextual, frequency and temporal factor of the data. The ability of users to interact, exchange ideas and opinions, and form social networks on the Web, has led systems to focus on the types of interactions these users have at the level of interaction between them as well as their social roles in the system. This social information is discussed and integrated into this research work. The impact and how they are integrated into the IR process are studied to improve the relevance of the results.

Footnote

Thèse de doctorat, Université du Québec à Chicoutimi.

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Content

This article reports an applied research on the construction and implementation of a semantically structured conceptual prototype to help in the organization and representation of human knowledge in hypertextual systems, based on four references: the Facet Analysis Theory (FAT), the Conceptual Map Theory, semantic structure of hypertext links and the technical guidelines of the Associacao Brasileira de Normas Técnicas (ABNT). This prototype, called Modelo Hipertextual para Organizacao de Documentos (MHTX) - Model For Hypertext Organization of Documents HTXM - is formed by a semantic structure called Conceptual Map (CM) and Expanded Summary (ES), the latter based on the summary of a selected doctoral thesis to which access points were designed. In the future, this prototype maybe used to implement a digital libraty called BTDECI - UFMG (Biblioteca de Teses e Dissertacöes do Programa de Pós-Graduacao da Escola de Ciência da Informacao da UFMG - Library of Theses and Dissertations of the Graduate Program of School of Information Science of Universidade Federal de Minas Gerais).

Type

a

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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.

Type

a

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Abstract

Nos últimos 30 anos, o tema das ontologias tem sido um dos terrenos mais férteis de investigação na área da Organização do Conhecimento. É um tema complexo e revestido de polémica, pela dificuldade na definição do próprio conceito e pelas apropriações que diferentes campos científicos têm exercido sobre ele. Com origem no domínio da filosofia, a ontologia é hoje um território partilhado pelas Ciências da Computação, com destaque para a Ciência dos Dados (Data Science), e pela Ciência da Informação, particularmente pela Organização do Conhecimento. São raros os autores desta área que não escreveram sobre o tema, abordando as suas fronteiras conceptuais ou discutindo a relação das ontologias com outros sistemas de organização do conhecimento, como as taxonomias, os tesauros ou as classificações.

Source

Boletim do Arquivo da Universidade de Coimbra 35(2022) no.1, S.191-198

Type

a

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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

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Date

14. 8.2011 13:33:22

Editor

Carroll, J.J. u. J. de Roo

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Abstract

Information management in corporate environments is a growing problem as companies' information assets grow and their need to use them in their operations. Several management models have been practiced with application on the most diverse fronts, practices that integrate the so-called Enterprise Content Management. This study proposes a conceptual model of semantic corporate information ecosystem, based on the Universal Document Model proposed by Dagobert Soergel. It focuses on unstructured information objects, especially multimedia, increasingly used in corporate environments, adding semantics and expanding their recovery potential in the composition and reuse of dynamic documents on demand. The proposed model considers stable elements in the organizational environment, such as actors, processes, business metadata and information objects, as well as some basic infrastructures of the corporate information environment. The main objective is to establish a conceptual model that adds semantic intelligence to information assets, leveraging pre-existing infrastructure in organizations, integrating and relating objects to other objects, actors and business processes. The approach methodology considered the state of the art of Information Organization, Representation and Retrieval, Organizational Content Management and Semantic Web technologies, in the scientific literature, as bases for the establishment of an integrative conceptual model. Therefore, the research will be qualitative and exploratory. The predicted steps of the model are: Environment, Data Type and Source Definition, Data Distillation, Metadata Enrichment, and Storage. As a result, in theoretical terms the extended model allows to process heterogeneous and unstructured data according to the established cut-outs and through the processes listed above, allowing value creation in the composition of dynamic information objects, with semantic aggregations to metadata.

Content

Tese de Doutorado apresentada ao Programa de Pós-Graduação da Universidade Federal Fluminense como requisito parcial para obtenção do título de Doutor em Ciência da Informação.

Imprint

Niteroi : UNIVERSIDADE FEDERAL FLUMINENSE / INSTITUTO DE ARTE E COMUNICAÇÃO SOCIAL / DEPARTAMENTO DE CIÊNCIA DA INFORMAÇÃO

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Abstract

Several instruments of knowledge organization will reflect different possibilities for information retrieval. In this context, ontologies have a different potential because they allow knowledge discovery, which can be used to retrieve information in a more flexible way. However, this potential can be affected by the theoretical principles adopted in ontology building. The aim of this paper is to discuss, in an introductory way, how a (not exhaustive) set of theoretical principles can influence an aspect of ontologies: their use to obtain inferences. In this context, the role of Ingetraut Dahlberg's Theory of Concept is discussed. The methodology is exploratory, qualitative, and from the technical point of view it uses bibliographic research supported by the content analysis method. It also presents a small example of application as a proof of concept. As results, a discussion about the influence of conceptual definition on subsumption inferences is presented, theoretical contributions are suggested that should be used to guide the formation of hierarchical structures on which such inferences are supported, and examples are provided of how the absence of such contributions can lead to erroneous inferences

Source

Ponto de Acesso, Salvador. 15(2021) no.3, S.344-380

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Abstract

Some of the fundamental activities of the software development process are related to the discipline of Requirements Engineering, whose objective is the discovery, analysis, documentation and verification of the requirements that will be part of the system. Requirements are the conditions or capabilities that software must have or perform to meet the users needs. The present study is being developed to propose a model of cooperation between Information Science and Requirements Engineering. Aims to present the analysis results on the possibilities of using the knowledge organization systems: taxonomies, thesauri and ontologies during the activities of Requirements Engineering: design, survey, elaboration, negotiation, specification, validation and requirements management. From the results obtained it was possible to identify in which stage of the Requirements Engineering process, each type of knowledge organization system could be used. We expect that this study put in evidence the need for new researchs and proposals to strengt the exchange between Information Science, as a science that has information as object of study, and the Requirements Engineering which has in the information the raw material to identify the informational needs of software users.

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a

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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.

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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.

Type

a

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Content

Programm mit Links auf die Präsentationen: Armando Stellato, Ahsan Morshed, Gudrun Johannsen, Yves Jacques, Caterina Caracciolo, Sachit Rajbhandari, Imma Subirats, Johannes Keizer: A Collaborative Framework for Managing and Publishing KOS - Christian Mader, Bernhard Haslhofer: Quality Criteria for Controlled Web Vocabularies - Ahsan Morshed, Benjamin Zapilko, Gudrun Johannsen, Philipp Mayr, Johannes Keizer: Evaluating approaches to automatically match thesauri from different domains for Linked Open Data - Johan De Smedt: SKOS extensions to cover mapping requirements - Mark Tomko: Translating biological data sets Into Linked Data - Daniel Kless: Ontologies and thesauri - similarities and differences - Antoine Isaac, Jacco van Ossenbruggen: Europeana and semantic alignment of vocabularies - Douglas Tudhope: Complementary use of ontologies and (other) KOS - Wilko van Hoek, Brigitte Mathiak, Philipp Mayr, Sascha Schüller: Comparing the accuracy of the semantic similarity provided by the Normalized Google Distance (NGD) and the Search Term Recommender (STR) - Denise Bedford: Selecting and Weighting Semantically Discovered Concepts as Social Tags - Stella Dextre Clarke, Johan De Smedt. ISO 25964-1: a new standard for development of thesauri and exchange of thesaurus data

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Abstract

The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.

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.

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Abstract

Hierarchical classifications, thesauri, and informal taxonomies are likely the most valuable input for creating, at reasonable cost, non-toy ontologies in many domains. They contain, readily available, a wealth of category definitions plus a hierarchy, and they reflect some degree of community consensus. However, their transformation into useful ontologies is not as straightforward as it appears. In this paper, we show that (1) it often depends on the context of usage whether an informal hierarchical categorization schema is a classification, a thesaurus, or a taxonomy, and (2) present a novel methodology for automatically deriving consistent RDF-S and OWL ontologies from such schemas. Finally, we (3) demonstrate the usefulness of this approach by transforming the two e-business categorization standards eCl@ss and UNSPSC into ontologies that overcome the limitations of earlier prototypes. Our approach allows for the script-based creation of meaningful ontology classes for a particular context while preserving the original hierarchy, even if the latter is not a real subsumption hierarchy in this particular context. Human intervention in the transformation is limited to checking some conceptual properties and identifying frequent anomalies, and the only input required is an informal categorization plus a notion of the target context. In particular, the approach does not require instance data, as ontology learning approaches would usually do.

Content

Vgl. unter: http://www.heppnetz.de/files/hepp-de-bruijn-ESWC2007-gentax-CRC.pdf.

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Abstract

We investigate different systems for extracting mathematical entities from English texts in the mathematical field of category theory as a first step for constructing a mathematical knowledge graph. We consider four different term extractors and compare their results. This small experiment showcases some of the issues with the construction and evaluation of terms extracted from noisy domain text. We also make available two open corpora in research mathematics, in particular in category theory: a small corpus of 755 abstracts from the journal TAC (3188 sentences), and a larger corpus from the nLab community wiki (15,000 sentences).

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a

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Footnote

Vgl.: http://www.ontoport.org/alfresco -> "My Home"; http://www.xing.com/t/de/ONTOLOGIEN

Type

a