Search (41 results, page 1 of 3)

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  1. Hannech, A.: Système de recherche d'information étendue basé sur une projection multi-espaces (2018) 0.05 
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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.
  2. Martins, S. de Castro: Modelo conceitual de ecossistema semântico de informações corporativas para aplicação em objetos multimídia (2019) 0.04 
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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
  3. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.04 
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    Abstract
    While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure - ontology - which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontology (LO) is an ontology representing a backbone taxonomy where the concept of the child node is more specific than the concept of the parent node. Formal lightweight ontologies can be generated from their informal ones. The key applications of formal lightweight ontologies are document classification, semantic search, and data integration. However, these applications suffer from the following problems: the disambiguation accuracy of the state of the art NLP tools used in generating formal lightweight ontologies from their informal ones; the lack of background knowledge needed for the formal lightweight ontologies; and the limitation of ontology reuse. In this dissertation, we propose a novel solution to these problems in formal lightweight ontologies; namely, faceted lightweight ontology (FLO). FLO is a lightweight ontology in which terms, present in each node label, and their concepts, are available in the background knowledge (BK), which is organized as a set of facets. A facet can be defined as a distinctive property of the groups of concepts that can help in differentiating one group from another. Background knowledge can be defined as a subset of a knowledge base, such as WordNet, and often represents a specific domain.
    Content
    PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
  4. Verwer, K.: Freiheit und Verantwortung bei Hans Jonas (2011) 0.04 
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    Content
    Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.
  5. Piros, A.: Az ETO-jelzetek automatikus interpretálásának és elemzésének kérdései (2018) 0.04 
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    Abstract
    Converting UDC numbers manually to a complex format such as the one mentioned above is an unrealistic expectation; supporting building these representations, as far as possible automatically, is a well-founded requirement. An additional advantage of this approach is that the existing records could also be processed and converted. In my dissertation I would like to prove also that it is possible to design and implement an algorithm that is able to convert pre-coordinated UDC numbers into the introduced format by identifying all their elements and revealing their whole syntactic structure as well. In my dissertation I will discuss a feasible way of building a UDC-specific XML schema for describing the most detailed and complicated UDC numbers (containing not only the common auxiliary signs and numbers, but also the different types of special auxiliaries). The schema definition is available online at: http://piros.udc-interpreter.hu#xsd. The primary goal of my research is to prove that it is possible to support building, retrieving, and analyzing UDC numbers without compromises, by taking the whole syntactic richness of the scheme by storing the UDC numbers reserving the meaning of pre-coordination. The research has also included the implementation of a software that parses UDC classmarks attended to prove that such solution can be applied automatically without any additional effort or even retrospectively on existing collections.
    Content
    Vgl. auch: New automatic interpreter for complex UDC numbers. Unter: <https%3A%2F%2Fudcc.org%2Ffiles%2FAttilaPiros_EC_36-37_2014-2015.pdf&usg=AOvVaw3kc9CwDDCWP7aArpfjrs5b>
  6. Schmolz, H.: Anaphora resolution and text retrieval : a lnguistic analysis of hypertexts (2015) 0.04 
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    Imprint
    Berlin : De Gruyter Mouton
  7. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.03 
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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.
  8. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.02 
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    Abstract
    After the launch of the World Wide Web, it became clear that searching documentson the Web would not be trivial. Well-known engines to search the web, like Google, focus on search in web documents using keywords. The documents are structured and indexed to ensure keywords match documents as accurately as possible. However, searching by keywords does not always suice. It is oen the case that users do not know exactly how to formulate the search query or which keywords guarantee retrieving the most relevant documents. Besides that, it occurs that users rather want to browse information than looking up something specific. It turned out that there is need for systems that enable more interactivity and facilitate the gradual refinement of search queries to explore the Web. Users expect more from the Web because the short keyword-based queries they pose during search, do not suffice for all cases. On top of that, the Web is changing structurally. The Web comprises, apart from a collection of documents, more and more linked data, pieces of information structured so they can be processed by machines. The consequently applied semantics allow users to exactly indicate machines their search intentions. This is made possible by describing data following controlled vocabularies, concept lists composed by experts, published uniquely identifiable on the Web. Even so, it is still not trivial to explore data on the Web. There is a large variety of vocabularies and various data sources use different terms to identify the same concepts.
    This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.
    The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. eries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research.
    Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data. There is a difference in the way users interact with resources, visually or textually, and how resources are represented for machines to be processed by algorithms. This difference complicates bridging the users' intents and machine executable queries. It is important to implement this 'translation' mechanism to impact the search as favorable as possible in terms of performance, complexity and accuracy. To do this, we explain a second technique, that supports such a bridging component. Our second technique is developed around three features that support the search process: looking up, relating and ranking resources. The main goal is to ensure that resources in the results are as precise and relevant as possible. During the evaluation of this technique, we did not only look at the precision of the search results but also investigated how the effectiveness of the search evolved while the user executed certain actions sequentially.
    When we speak about finding relationships between resources, it is necessary to dive deeper in the structure. The graph structure of linked data where the semantics give meaning to the relationships between resources enable the execution of pathfinding algorithms. The assigned weights and heuristics are base components of such algorithms and ultimately define (the order) which resources are included in a path. These paths explain indirect connections between resources. Our third technique proposes an algorithm that optimizes the choice of resources in terms of serendipity. Some optimizations guard the consistence of candidate-paths where the coherence of consecutive connections is maximized to avoid trivial and too arbitrary paths. The implementation uses the A* algorithm, the de-facto reference when it comes to heuristically optimized minimal cost paths. The effectiveness of paths was measured based on common automatic metrics and surveys where the users could indicate their preference for paths, generated each time in a different way. Finally, all our techniques are applied to a use case about publications in digital libraries where they are aligned with information about scientific conferences and researchers. The application to this use case is a practical example because the different aspects of exploratory search come together. In fact, the techniques also evolved from the experiences when implementing the use case. Practical details about the semantic model are explained and the implementation of the search system is clarified module by module. The evaluation positions the result, a prototype of a tool to explore scientific publications, researchers and conferences next to some important alternatives.
    Content
    Proefschrift ingediend tot het behalen van de graad van Doctor in de ingenieurswetenschappen: computerwetenschappen. Vgl. unter: https://www.researchgate.net/publication/319667837_Exploring_semantic_relationships_in_the_web_of_data.
  9. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.02 
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    Abstract
    In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.
    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
  10. Bertram, J.: Informationen verzweifelt gesucht : Enterprise Search in österreichischen Großunternehmen (2011) 0.02 
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    Abstract
    Die Arbeit geht dem Status quo der unternehmensweiten Suche in österreichischen Großunternehmen nach und beleuchtet Faktoren, die darauf Einfluss haben. Aus der Analyse des Ist-Zustands wird der Bedarf an Enterprise-Search-Software abgeleitet und es werden Rahmenbedingungen für deren erfolgreiche Einführung skizziert. Die Untersuchung stützt sich auf eine im Jahr 2009 durchgeführte Onlinebefragung von 469 österreichischen Großunternehmen (Rücklauf 22 %) und daran anschließende Leitfadeninterviews mit zwölf Teilnehmern der Onlinebefragung. Der theoretische Teil verortet die Arbeit im Kontext des Informations- und Wissensmanagements. Der Fokus liegt auf dem Ansatz der Enterprise Search, ihrer Abgrenzung gegenüber der Suche im Internet und ihrem Leistungsspektrum. Im empirischen Teil wird zunächst aufgezeigt, wie die Unternehmen ihre Informationen organisieren und welche Probleme dabei auftreten. Es folgt eine Analyse des Status quo der Informati-onssuche im Unternehmen. Abschließend werden Bekanntheit und Einsatz von Enterprise-Search-Software in der Zielgruppe untersucht sowie für die Einführung dieser Software nötige Rahmenbedingungen benannt. Defizite machen die Befragten insbesondere im Hinblick auf die übergreifende Suche im Unternehmen und die Suche nach Kompetenzträgern aus. Hier werden Lücken im Wissensmanagement offenbar. 29 % der Respondenten der Onlinebefragung geben zu-dem an, dass es in ihren Unternehmen gelegentlich bis häufig zu Fehlentscheidungen infolge defizitärer Informationslagen kommt. Enterprise-Search-Software kommt in 17 % der Unternehmen, die sich an der Onlinebefragung beteiligten, zum Einsatz. Die durch Enterprise-Search-Software bewirkten Veränderungen werden grundsätzlich posi-tiv beurteilt. Alles in allem zeigen die Ergebnisse, dass Enterprise-Search-Strategien nur Erfolg haben können, wenn man sie in umfassende Maßnahmen des Informations- und Wissensmanagements einbettet.
    Date
    22. 1.2016 20:40:31
    Location
    A
  11. Shala, E.: ¬Die Autonomie des Menschen und der Maschine : gegenwärtige Definitionen von Autonomie zwischen philosophischem Hintergrund und technologischer Umsetzbarkeit (2014) 0.01 
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    Footnote
    Vgl. unter: https://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=2ahUKEwizweHljdbcAhVS16QKHXcFD9QQFjABegQICRAB&url=https%3A%2F%2Fwww.researchgate.net%2Fpublication%2F271200105_Die_Autonomie_des_Menschen_und_der_Maschine_-_gegenwartige_Definitionen_von_Autonomie_zwischen_philosophischem_Hintergrund_und_technologischer_Umsetzbarkeit_Redigierte_Version_der_Magisterarbeit_Karls&usg=AOvVaw06orrdJmFF2xbCCp_hL26q.
  12. Geisriegler, E.: Enriching electronic texts with semantic metadata : a use case for the historical Newspaper Collection ANNO (Austrian Newspapers Online) of the Austrian National Libraryhek (2012) 0.01 
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    Date
    3. 2.2013 18:00:22
    Location
    A
  13. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.01 
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    Abstract
    Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
    Modular ontologies are built in modular manner by combining modules from multiple relevant ontologies. Ontology heterogeneity also arises during modular ontology construction because multiple ontologies are being dealt with, during this process. Ontologies need to be aligned before using them for modular ontology construction. The existing approaches for ontology alignment compare all the concepts of each ontology to be aligned, hence not optimized in terms of time and search space utilization. A new indexing technique is proposed based on modular ontology. An efficient ontology alignment technique is proposed to solve the heterogeneity problem during the construction of modular ontology. Results are satisfactory as Precision and Recall are improved by (8%) and (10%) respectively. The value of Pearsons Correlation Coefficient for degree of similarity, time, search space requirement, precision and recall are close to 1 which shows that the results are significant. Further research can be carried out for using modular ontology based indexing technique for Multimedia Information Retrieval and Bio-Medical information retrieval.
    Date
    20. 1.2015 18:30:22
  14. Glaesener, L.: Automatisches Indexieren einer informationswissenschaftlichen Datenbank mit Mehrwortgruppen (2012) 0.01 
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    Date
    11. 9.2012 19:43:22
  15. Tavakolizadeh-Ravari, M.: Analysis of the long term dynamics in thesaurus developments and its consequences (2017) 0.01 
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    Content
    Vgl.: https://www.ibi.hu-berlin.de/de/archiv/forschung/prom_habil/dissertationen/Tavakolizadeh-Ravari2007. Vgl. auch: http://mravari.blogfa.com/post-20.aspxgl.
  16. Köbler, J.; Niederklapfer, T.: Kreuzkonkordanzen zwischen RVK-BK-MSC-PACS der Fachbereiche Mathematik un Physik (2010) 0.01 
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    Pages
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  17. Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013) 0.01 
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    Date
    4. 2.2015 9:22:39
  18. Onofri, A.: Concepts in context (2013) 0.00 
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    Abstract
    My thesis discusses two related problems that have taken center stage in the recent literature on concepts: 1) What are the individuation conditions of concepts? Under what conditions is a concept Cv(1) the same concept as a concept Cv(2)? 2) What are the possession conditions of concepts? What conditions must be satisfied for a thinker to have a concept C? The thesis defends a novel account of concepts, which I call "pluralist-contextualist": 1) Pluralism: Different concepts have different kinds of individuation and possession conditions: some concepts are individuated more "coarsely", have less demanding possession conditions and are widely shared, while other concepts are individuated more "finely" and not shared. 2) Contextualism: When a speaker ascribes a propositional attitude to a subject S, or uses his ascription to explain/predict S's behavior, the speaker's intentions in the relevant context determine the correct individuation conditions for the concepts involved in his report. In chapters 1-3 I defend a contextualist, non-Millian theory of propositional attitude ascriptions. Then, I show how contextualism can be used to offer a novel perspective on the problem of concept individuation/possession. More specifically, I employ contextualism to provide a new, more effective argument for Fodor's "publicity principle": if contextualism is true, then certain specific concepts must be shared in order for interpersonally applicable psychological generalizations to be possible. In chapters 4-5 I raise a tension between publicity and another widely endorsed principle, the "Fregean constraint" (FC): subjects who are unaware of certain identity facts and find themselves in so-called "Frege cases" must have distinct concepts for the relevant object x. For instance: the ancient astronomers had distinct concepts (HESPERUS/PHOSPHORUS) for the same object (the planet Venus). First, I examine some leading theories of concepts and argue that they cannot meet both of our constraints at the same time. Then, I offer principled reasons to think that no theory can satisfy (FC) while also respecting publicity. (FC) appears to require a form of holism, on which a concept is individuated by its global inferential role in a subject S and can thus only be shared by someone who has exactly the same inferential dispositions as S. This explains the tension between publicity and (FC), since holism is clearly incompatible with concept shareability. To solve the tension, I suggest adopting my pluralist-contextualist proposal: concepts involved in Frege cases are holistically individuated and not public, while other concepts are more coarsely individuated and widely shared; given this "plurality" of concepts, we will then need contextual factors (speakers' intentions) to "select" the specific concepts to be employed in our intentional generalizations in the relevant contexts. In chapter 6 I develop the view further by contrasting it with some rival accounts. First, I examine a very different kind of pluralism about concepts, which has been recently defended by Daniel Weiskopf, and argue that it is insufficiently radical. Then, I consider the inferentialist accounts defended by authors like Peacocke, Rey and Jackson. Such views, I argue, are committed to an implausible picture of reference determination, on which our inferential dispositions fix the reference of our concepts: this leads to wrong predictions in all those cases of scientific disagreement where two parties have very different inferential dispositions and yet seem to refer to the same natural kind.
  19. Castellanos Ardila, J.P.: Investigation of an OSLC-domain targeting ISO 26262 : focus on the left side of the software V-model (2016) 0.00 
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    Abstract
    Industries have adopted a standardized set of practices for developing their products. In the automotive domain, the provision of safety-compliant systems is guided by ISO 26262, a standard that specifies a set of requirements and recommendations for developing automotive safety-critical systems. For being in compliance with ISO 26262, the safety lifecycle proposed by the standard must be included in the development process of a vehicle. Besides, a safety case that shows that the system is acceptably safe has to be provided. The provision of a safety case implies the execution of a precise documentation process. This process makes sure that the work products are available and traceable. Further, the documentation management is defined in the standard as a mandatory activity and guidelines are proposed/imposed for its elaboration. It would be appropriate to point out that a well-documented safety lifecycle will provide the necessary inputs for the generation of an ISO 26262-compliant safety case. The OSLC (Open Services for Lifecycle Collaboration) standard and the maturing stack of semantic web technologies represent a promising integration platform for enabling semantic interoperability between the tools involved in the safety lifecycle. Tools for requirements, architecture, development management, among others, are expected to interact and shared data with the help of domains specifications created in OSLC. This thesis proposes the creation of an OSLC tool-chain infrastructure for sharing safety-related information, where fragments of safety information can be generated. The steps carried out during the elaboration of this master thesis consist in the identification, representation, and shaping of the RDF resources needed for the creation of a safety case. The focus of the thesis is limited to a tiny portion of the ISO 26262 left-hand side of the V-model, more exactly part 6 clause 8 of the standard: Software unit design and implementation. Regardless of the use of a restricted portion of the standard during the execution of this thesis, the findings can be extended to other parts, and the conclusions can be generalize. This master thesis is considered one of the first steps towards the provision of an OSLC-based and ISO 26262-compliant methodological approach for representing and shaping the work products resulting from the execution of the safety lifecycle, documentation required in the conformation of an ISO-compliant safety case.
  20. Thornton, K: Powerful structure : inspecting infrastructures of information organization in Wikimedia Foundation projects (2016) 0.00 
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    Abstract
    This dissertation investigates the social and technological factors of collaboratively organizing information in commons-based peer production systems. To do so, it analyzes the diverse strategies that members of Wikimedia Foundation (WMF) project communities use to organize information. Key findings from this dissertation show that conceptual structures of information organization are encoded into the infrastructure of WMF projects. The fact that WMF projects are commons-based peer production systems means that we can inspect the code that enables these systems, but a specific type of technical literacy is required to do so. I use three methods in this dissertation. I conduct a qualitative content analysis of the discussions surrounding the design, implementation and evaluation of the category system; a quantitative analysis using descriptive statistics of patterns of editing among editors who contributed to the code of templates for information boxes; and a close reading of the infrastructure used to create the category system, the infobox templates, and the knowledge base of structured data.
    Footnote
    A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington.

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