Search (8 results, page 1 of 1)

  • × theme_ss:"Suchmaschinen"
  • × type_ss:"el"
  • × year_i:[2010 TO 2020}
  1. Franke-Maier, M.; Rüter, C.: Discover Sacherschließung! : Was machen suchmaschinenbasierte Systeme mit unseren inhaltlichen Metadaten? (2015) 0.04 
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    Date
    2. 3.2015 10:29:44
    Source
    http://opus4.kobv.de/opus4-hsog/frontdoor/index/index/docId/1124
  2. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.01 
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    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
  3. Li, Z.: ¬A domain specific search engine with explicit document relations (2013) 0.01 
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    Abstract
    The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.
  4. Mandalka, M.: Open semantic search zum unabhängigen und datenschutzfreundlichen Erschliessen von Dokumenten (2015) 0.00 
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    Content
    Virtuelle Maschine für mehr Plattformunabhängigkeit Die nun auch deutschsprachig verfügbare und mit deutschen Daten wie Ortsnamen oder Bundestagsabgeordneten vorkonfigurierte virtuelle Maschine Open Semantic Desktop Search ermöglicht nun auch auf einzelnen Desktop Computern oder Notebooks mit Windows oder iOS (Mac) die Suche und Analyse von Dokumenten mit der Suchmaschine Open Semantic Search. Als virtuelle Maschine (VM) lässt sich die Suchmaschine Open Semantic Search nicht nur für besonders sensible Dokumente mit dem verschlüsselten Live-System InvestigateIX als abgeschottetes System auf verschlüsselten externen Datenträgern installieren, sondern als virtuelle Maschine für den Desktop auch einfach unter Windows oder auf einem Mac in eine bzgl. weiterer Software und Daten bereits existierende Systemumgebung integrieren, ohne hierzu auf einen (für gemeinsame Recherchen im Team oder für die Redaktion auch möglichen) Suchmaschinen Server angewiesen zu sein. Datenschutz & Unabhängigkeit: Grössere Unabhängigkeit von zentralen IT-Infrastrukturen für unabhängigen investigativen Datenjournalismus Damit ist investigative Recherche weitmöglichst unabhängig möglich: ohne teure, zentrale und von Administratoren abhängige Server, ohne von der Dokumentenanzahl abhängige teure Software-Lizenzen, ohne Internet und ohne spionierende Cloud-Dienste. Datenanalyse und Suche finden auf dem eigenen Computer statt, nicht wie bei vielen anderen Lösungen in der sogenannten Cloud."
  5. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.00 
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    Date
    17.12.2013 11:02:22
  6. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.00 
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    Date
    19. 2.2019 17:22:00
  7. Günther, M.: Vermitteln Suchmaschinen vollständige Bilder aktueller Themen? : Untersuchung der Gewichtung inhaltlicher Aspekte von Suchmaschinenergebnissen in Deutschland und den USA (2016) 0.00 
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    Source
    Young information scientists. 1(2016), S.13-29
  8. Gillitzer, B.: Yewno (2017) 0.00 
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    Date
    22. 2.2017 10:16:49

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