Search (38 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Semantic Web"
  • × type_ss:"a"
  1. Mayr, P.; Mutschke, P.; Petras, V.: Reducing semantic complexity in distributed digital libraries : Treatment of term vagueness and document re-ranking (2008) 0.02
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    Abstract
    Purpose - The general science portal "vascoda" merges structured, high-quality information collections from more than 40 providers on the basis of search engine technology (FAST) and a concept which treats semantic heterogeneity between different controlled vocabularies. First experiences with the portal show some weaknesses of this approach which come out in most metadata-driven Digital Libraries (DLs) or subject specific portals. The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value-added services (treatment of term vagueness and document re-ranking) that gain a certain quality in DLs if they are combined with heterogeneity components established in the project "Competence Center Modeling and Treatment of Semantic Heterogeneity". Design/methodology/approach - Two methods, which are derived from scientometrics and network analysis, will be implemented with the objective to re-rank result sets by the following structural properties: the ranking of the results by core journals (so-called Bradfordizing) and ranking by centrality of authors in co-authorship networks. Findings - The methods, which will be implemented, focus on the query and on the result side of a search and are designed to positively influence each other. Conceptually, they will improve the search quality and guarantee that the most relevant documents in result sets will be ranked higher. Originality/value - The central impact of the paper focuses on the integration of three structural value-adding methods, which aim at reducing the semantic complexity represented in distributed DLs at several stages in the information retrieval process: query construction, search and ranking and re-ranking.
  2. Ning, X.; Jin, H.; Wu, H.: RSS: a framework enabling ranked search on the semantic web (2008) 0.01
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    Abstract
    The semantic web not only contains resources but also includes the heterogeneous relationships among them, which is sharply distinguished from the current web. As the growth of the semantic web, specialized search techniques are of significance. In this paper, we present RSS-a framework for enabling ranked semantic search on the semantic web. In this framework, the heterogeneity of relationships is fully exploited to determine the global importance of resources. In addition, the search results can be greatly expanded with entities most semantically related to the query, thus able to provide users with properly ordered semantic search results by combining global ranking values and the relevance between the resources and the query. The proposed semantic search model which supports inference is very different from traditional keyword-based search methods. Moreover, RSS also distinguishes from many current methods of accessing the semantic web data in that it applies novel ranking strategies to prevent returning search results in disorder. The experimental results show that the framework is feasible and can produce better ordering of semantic search results than directly applying the standard PageRank algorithm on the semantic web.
  3. Wang, H.; Liu, Q.; Penin, T.; Fu, L.; Zhang, L.; Tran, T.; Yu, Y.; Pan, Y.: Semplore: a scalable IR approach to search the Web of Data (2009) 0.01
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    Abstract
    The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.
  4. Sah, M.; Wade, V.: Personalized concept-based search on the Linked Open Data (2015) 0.01
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    Abstract
    In this paper, we present a novel personalized concept-based search mechanism for the Web of Data based on results categorization. The innovation of the paper comes from combining novel categorization and personalization techniques, and using categorization for providing personalization. In our approach, search results (Linked Open Data resources) are dynamically categorized into Upper Mapping and Binding Exchange Layer (UMBEL) concepts using a novel fuzzy retrieval model. Then, results with the same concepts are grouped together to form categories, which we call conceptlenses. Such categorization enables concept-based browsing of the retrieved results aligned to users' intent or interests. When the user selects a concept lens for exploration, results are immediately personalized. In particular, all concept lenses are personally re-organized according to their similarity to the selected lens. Within the selected concept lens; more relevant results are included using results re-ranking and query expansion, as well as relevant concept lenses are suggested to support results exploration. This allows dynamic adaptation of results to the user's local choices. We also support interactive personalization; when the user clicks on a result, within the interacted lens, relevant lenses and results are included using results re-ranking and query expansion. Extensive evaluations were performed to assess our approach: (i) Performance of our fuzzy-based categorization approach was evaluated on a particular benchmark (~10,000 mappings). The evaluations showed that we can achieve highly acceptable categorization accuracy and perform better than the vector space model. (ii) Personalized search efficacy was assessed using a user study with 32 participants in a tourist domain. The results revealed that our approach performed significantly better than a non-adaptive baseline search. (iii) Dynamic personalization performance was evaluated, which illustrated that our personalization approach is scalable. (iv) Finally, we compared our system with the existing LOD search engines, which showed that our approach is unique.
  5. Krause, J.: Shell Model, Semantic Web and Web Information Retrieval (2006) 0.01
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    Abstract
    The middle of the 1990s are coined by the increased enthusiasm for the possibilities of the WWW, which has only recently deviated - at least in relation to scientific information - for the differentiated measuring of its advantages and disadvantages. Web Information Retrieval originated as a specialized discipline with great commercial significance (for an overview see Lewandowski 2005). Besides the new technological structure that enables the indexing and searching (in seconds) of unimaginable amounts of data worldwide, new assessment processes for the ranking of search results are being developed, which use the link structures of the Web. They are the main innovation with respect to the traditional "mother discipline" of Information Retrieval. From the beginning, link structures of Web pages are applied to commercial search engines in a wide array of variations. From the perspective of scientific information, link topology based approaches were in essence trying to solve a self-created problem: on the one hand, it quickly became clear that the openness of the Web led to an up-tonow unknown increase in available information, but this also caused the quality of the Web pages searched to become a problem - and with it the relevance of the results. The gatekeeper function of traditional information providers, which narrows down every user query to focus on high-quality sources was lacking. Therefore, the recognition of the "authoritativeness" of the Web pages by general search engines such as Google was one of the most important factors for their success.
  6. Oliveira Machado, L.M.; Souza, R.R.; Simões, M. da Graça: Semantic web or web of data? : a diachronic study (1999 to 2017) of the publications of Tim Berners-Lee and the World Wide Web Consortium (2019) 0.01
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    Abstract
    The web has been, in the last decades, the place where information retrieval achieved its maximum importance, given its ubiquity and the sheer volume of information. However, its exponential growth made the retrieval task increasingly hard, relying in its effectiveness on idiosyncratic and somewhat biased ranking algorithms. To deal with this problem, a "new" web, called the Semantic Web (SW), was proposed, bringing along concepts like "Web of Data" and "Linked Data," although the definitions and connections among these concepts are often unclear. Based on a qualitative approach built over a literature review, a definition of SW is presented, discussing the related concepts sometimes used as synonyms. It concludes that the SW is a comprehensive and ambitious construct that includes the great purpose of making the web a global database. It also follows the specifications developed and/or associated with its operationalization and the necessary procedures for the connection of data in an open format on the web. The goals of this comprehensive SW are the union of two outcomes still tenuously connected: the virtually unlimited possibility of connections between data-the web domain-with the potentiality of the automated inference of "intelligent" systems-the semantic component.
  7. Malmsten, M.: Making a library catalogue part of the Semantic Web (2008) 0.01
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    Date
    20. 2.2009 10:29:39
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  8. Hooland, S. van; Verborgh, R.; Wilde, M. De; Hercher, J.; Mannens, E.; Wa, R.Van de: Evaluating the success of vocabulary reconciliation for cultural heritage collections (2013) 0.01
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    Date
    22. 3.2013 19:29:20
  9. Papadakis, I. et al.: Highlighting timely information in libraries through social and semantic Web technologies (2016) 0.00
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  10. Tennis, J.T.: Scheme versioning in the Semantic Web (2006) 0.00
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    Date
    23.12.2007 10:14:29
  11. Stamou, G.; Chortaras, A.: Ontological query answering over semantic data (2017) 0.00
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    Pages
    S.29-63
  12. Siwecka, D.: Knowledge organization systems used in European national libraries towards interoperability of the semantic Web (2018) 0.00
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    Date
    18. 1.2019 18:46:29
  13. Aslam, S.; Sonkar, S.K.: Semantic Web : an overview (2019) 0.00
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    Date
    10.12.2020 9:29:12
  14. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.00
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    Date
    31. 7.2010 16:58:22
  15. Ilik, V.: Distributed person data : using Semantic Web compliant data in subject name headings (2015) 0.00
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    Date
    8.11.2015 21:30:29
    Source
    Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
  16. O'Hara, K.; Hall, W.: Semantic Web (2009) 0.00
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    Date
    27. 8.2011 14:29:18
  17. Dunsire, G.: FRBR and the Semantic Web (2012) 0.00
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    Date
    29. 5.2015 10:50:02
  18. Wenige, L.: ¬The application of linked data resources for library recommender systems (2017) 0.00
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    Source
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  19. Kushwaha, N.; Vyas, O.P.: SemMovieRec : extraction of semantic features of DBpedia for recommender system (2017) 0.00
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  20. Marcondes, C.H.: Representing and organizing scientific knowledge in biomedical articles with Semantic Web technologies (2017) 0.00
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