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  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × type_ss:"el"
  1. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.04 
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    Abstract
    Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
    Date
    11. 2.2011 18:22:25
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Gillitzer, B.: Yewno (2017) 0.03 
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    Abstract
    Yewno findet Themen und Konzepte (Suchbegriffe und ihre Abstraktionen) in englischsprachigen digitalen Texten mit Methoden des maschinellen Lernens und der künstlichen Intelligenz. Als Ergebnis Ihrer Suchanfrage werden die Konzepte, die Ihre Anfrage betreffen, in vielfältigen sachlichen Beziehungen als graphisches Netzwerk präsentiert, über das Sie einfach navigieren können. Auch versteckte thematische Beziehungen werden hier sichtbar gemacht, die vom Bekannten zu neuen Entdeckungen führen. Im Rahmen einer Pilotphase können Sie über einen interdisziplinären Ausschnitt aus aktuellen englischsprachigen Fachzeitschriften verschiedenster Fachgebiete recherchieren. Die zu den Themen gehörigen Artikel werden in Ausschnitten unmittelbar angezeigt und können in den meisten Fällen direkt als Volltext aufgerufen werden.
    "Die Bayerische Staatsbibliothek testet den semantischen "Discovery Service" Yewno als zusätzliche thematische Suchmaschine für digitale Volltexte. Der Service ist unter folgendem Link erreichbar: https://www.bsb-muenchen.de/recherche-und-service/suchen-und-finden/yewno/. Das Identifizieren von Themen, um die es in einem Text geht, basiert bei Yewno alleine auf Methoden der künstlichen Intelligenz und des maschinellen Lernens. Dabei werden sie nicht - wie bei klassischen Katalogsystemen - einem Text als Ganzem zugeordnet, sondern der jeweiligen Textstelle. Die Eingabe eines Suchwortes bzw. Themas, bei Yewno "Konzept" genannt, führt umgehend zu einer grafischen Darstellung eines semantischen Netzwerks relevanter Konzepte und ihrer inhaltlichen Zusammenhänge. So ist ein Navigieren über thematische Beziehungen bis hin zu den Fundstellen im Text möglich, die dann in sogenannten Snippets angezeigt werden. In der Test-Anwendung der Bayerischen Staatsbibliothek durchsucht Yewno aktuell 40 Millionen englischsprachige Dokumente aus Publikationen namhafter Wissenschaftsverlage wie Cambridge University Press, Oxford University Press, Wiley, Sage und Springer, sowie Dokumente, die im Open Access verfügbar sind. Nach der dreimonatigen Testphase werden zunächst die Rückmeldungen der Nutzer ausgewertet. Ob und wann dann der Schritt von der klassischen Suchmaschine zum semantischen "Discovery Service" kommt und welche Bedeutung Anwendungen wie Yewno in diesem Zusammenhang einnehmen werden, ist heute noch nicht abzusehen. Die Software Yewno wurde vom gleichnamigen Startup in Zusammenarbeit mit der Stanford University entwickelt, mit der auch die Bayerische Staatsbibliothek eng kooperiert. [Inetbib-Posting vom 22.02.2017].
    Date
    22. 2.2017 10:16:49
    Source
    https://www.bsb-muenchen.de/recherche-und-service/suchen-und-finden/yewno/
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. Kasprzik, A.; Kett, J.: Vorschläge für eine Weiterentwicklung der Sacherschließung und Schritte zur fortgesetzten strukturellen Aufwertung der GND (2018) 0.02 
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    Abstract
    Aufgrund der fortgesetzten Publikationsflut stellt sich immer dringender die Frage, wie die Schwellen für die Titel- und Normdatenpflege gesenkt werden können - sowohl für die intellektuelle als auch die automatisierte Sacherschließung. Zu einer Verbesserung der Daten- und Arbeitsqualität in der Sacherschließung kann beigetragen werden a) durch eine flexible Visualisierung der Gemeinsamen Normdatei (GND) und anderer Wissensorganisationssysteme, so dass deren Graphstruktur intuitiv erfassbar wird, und b) durch eine investigative Analyse ihrer aktuellen Struktur und die Entwicklung angepasster automatisierter Methoden zur Ermittlung und Korrektur fehlerhafter Muster. Die Deutsche Nationalbibliothek (DNB) prüft im Rahmen des GND-Entwicklungsprogramms 2017-2021, welche Bedingungen für eine fruchtbare community-getriebene Open-Source-Entwicklung entsprechender Werkzeuge gegeben sein müssen. Weiteres Potential steckt in einem langfristigen Übergang zu einer Darstellung von Titel- und Normdaten in Beschreibungssprachen im Sinne des Semantic Web (RDF; OWL, SKOS). So profitiert die GND von der Interoperabilität mit anderen kontrollierten Vokabularen und von einer erleichterten Interaktion mit anderen Fach-Communities und kann umgekehrt auch außerhalb des Bibliothekswesens zu einem noch attraktiveren Wissensorganisationssystem werden. Darüber hinaus bieten die Ansätze aus dem Semantic Web die Möglichkeit, stärker formalisierte, strukturierende Satellitenvokabulare rund um die GND zu entwickeln. Daraus ergeben sich nicht zuletzt auch neue Perspektiven für die automatisierte Sacherschließung. Es wäre lohnend, näher auszuloten, wie und inwieweit semantisch-logische Verfahren den bestehenden Methodenmix bereichern können.
    Content
    Vortrag anlässlich des 107. Deutschen Bibliothekartages 2018 in Berlin, Themenkreis "Fokus Erschließen & Bewahren". https://www.o-bib.de/article/view/5390/7450. https://doi.org/10.5282/o-bib/2018H4S127-140.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Mandalka, M.: Open semantic search zum unabhängigen und datenschutzfreundlichen Erschliessen von Dokumenten (2015) 0.02 
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    Abstract
    Ob grösserer Leak oder Zusammenwürfeln oder (wieder) Erschliessen umfangreicherer (kollaborativer) Recherche(n) oder Archive: Immer öfter müssen im Journalismus größere Datenberge und Dokumentenberge erschlossen werden. In eine Suchmaschine integrierte Analyse-Tools helfen (halb)automatisch.
    Content
    "Open Semantic Desktop Search Zur Tagung des Netzwerk Recherche ist die Desktop Suchmaschine Open Semantic Desktop Search zum unabhängigen und datenschutzfreundlichen Erschliessen und Analysieren von Dokumentenbergen nun erstmals auch als deutschsprachige Version verfügbar. Dank mächtiger Open Source Basis kann die auf Debian GNU/Linux und Apache Solr basierende freie Software als unter Linux, Windows oder Mac lauffähige virtuelle Maschine kostenlos heruntergeladen, genutzt, weitergegeben und weiterentwickelt werden. Dokumentenberge erschliessen Ob grösserer Leak oder Zusammenwürfeln oder (wieder) Erschliessen umfangreicherer (kollaborativer) Recherche(n) oder Archive: Hin und wieder müssen größere Datenberge bzw. Dokumentenberge erschlossen werden, die so viele Dokumente enthalten, dass Mensch diese Masse an Dokumenten nicht mehr alle nacheinander durchschauen und einordnen kann. Auch bei kontinuierlicher Recherche zu Fachthemen sammeln sich mit der Zeit größere Mengen digitalisierter oder digitaler Dokumente zu grösseren Datenbergen an, die immer weiter wachsen und deren Informationen mit einer Suchmaschine für das Archiv leichter auffindbar bleiben. Moderne Tools zur Datenanalyse in Verbindung mit Enterprise Search Suchlösungen und darauf aufbauender Recherche-Tools helfen (halb)automatisch.
    Unabhängiges Durchsuchen und Analysieren grosser Datenmengen Damit können investigativ arbeitende Journalisten selbstständig und auf eigener Hardware datenschutzfreundlich hunderte, tausende, hunderttausende oder gar Millionen von Dokumenten oder hunderte Megabyte, Gigabytes oder gar einige Terabytes an Daten mit Volltextsuche durchsuchbar machen. Automatische Datenanreicherung und Erschliessung mittels Hintergrundwissen Zudem wird anhand von konfigurierbaren Hintergrundwissen automatisch eine interaktive Navigation zu in Dokumenten enthaltenen Namen von Bundestagsabgeordneten oder Orten in Deutschland generiert oder anhand Textmustern strukturierte Informationen wie Geldbeträge extrahiert. Mittels Named Entities Manager für Personen, Organisationen, Begriffe und Orte können eigene Rechercheschwerpunkte konfiguriert werden, aus denen dann automatisch eine interaktive Navigation (Facettensuche) und aggregierte Übersichten generiert werden. Automatische Datenvisualisierung Diese lassen sich auch visualisieren: So z.B. die zeitliche Verteilung von Suchergebnissen als Trand Diagramm oder durch gleichzeitige Nennung in Dokumenten abgeleitete Verbindungen als Netzwerk bzw. Graph.
    Automatische Texterkennung (OCR) Dokumente, die nicht im Textformat, sondern als Grafiken vorliegen, wie z.B. Scans werden automatisch durch automatische Texterkennung (OCR) angereichert und damit auch der extrahierte Text durchsuchbar. Auch für eingebettete Bilddateien bzw. Scans innerhalb von PDF-Dateien. Unscharfe Suche mit Listen Ansonsten ist auch das Recherche-Tool bzw. die Such-Applikation "Suche mit Listen" integriert, mit denen sich schnell und komfortabel abgleichen lässt, ob es zu den einzelnen Einträgen in Listen jeweils Treffer in der durchsuchbaren Dokumentensammlung gibt. Mittels unscharfer Suche findet das Tool auch Ergebnisse, die in fehlerhaften oder unterschiedlichen Schreibweisen vorliegen. Semantische Suche und Textmining Im Recherche, Textanalyse und Document Mining Tutorial zu den enthaltenen Recherche-Tools und verschiedenen kombinierten Methoden zur Datenanalyse, Anreicherung und Suche wird ausführlicher beschrieben, wie auch eine große heterogene und unstrukturierte Dokumentensammlung bzw. eine grosse Anzahl von Dokumenten in verschiedenen Formaten leicht durchsucht und analysiert werden kann.
    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."
    Source
    http://www.linux-community.de/Internal/Nachrichten/Open-Semantic-Search-zum-unabhaengigen-und-datenschutzfreundlichen-Erschliessen-von-Dokumenten
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013) 0.01 
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    Abstract
    Dieser Artikel adressiert einen Randbereich des Wissensmanagements: die Schnittstelle zwischen Unternehmens-externen Informationen im Internet und den Leistungsprozessen eines Unternehmens. Diese Schnittstelle ist besonders für Unternehmen von Interesse, deren Leistungsprozesse von externen Informationen abhängen und die auf diese Prozesse angewiesen sind. Wir zeigen an zwei Fallbeispielen, dass die inhaltliche Filterung von Informationen beim Eintritt ins Unternehmen ein wichtiges Werkzeug darstellt, um daran anschließende Wissens- und Informationsmanagementprozesse effizient zu gestalten.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  6. Michel, D.: Taxonomy of Subject Relationships (1997) 0.01 
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Konzeption und Anwendung des Prinzips Thesaurus
  7. Tudhope, D.; Alani, H.; Jones, C.: Augmenting thesaurus relationships : possibilities for retrieval (2001) 0.01 
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    Abstract
    This paper discusses issues concerning the augmentation of thesaurus relationships, in light of new application possibilities for retrieval. We first discuss a case study that explored the retrieval potential of an augmented set of thesaurus relationships by specialising standard relationships into richer subtypes, in particular hierarchical geographical containment and the associative relationship. We then locate this work in a broader context by reviewing various attempts to build taxonomies of thesaurus relationships, and conclude by discussing the feasibility of hierarchically augmenting the core set of thesaurus relationships, particularly the associative relationship. We discuss the possibility of enriching the specification and semantics of Related Term (RT relationships), while maintaining compatibility with traditional thesauri via a limited hierarchical extension of the associative (and hierarchical) relationships. This would be facilitated by distinguishing the type of term from the (sub)type of relationship and explicitly specifying semantic categories for terms following a faceted approach. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but also the problem of uncontrolled expansion of query term sets. Results presented in this paper suggest the potential for taking account of the hierarchical context of an RT link and specialisations of the RT relationship
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Konzeption und Anwendung des Prinzips Thesaurus
  8. Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006) 0.01 
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    Abstract
    This paper addresses the problem of information discovery in large collections of text. For users, one of the key problems in working with such collections is determining where to focus their attention. In selecting documents for examination, users must be able to formulate reasonably precise queries. Queries that are too broad will greatly reduce the efficiency of information discovery efforts by overwhelming the users with peripheral information. In order to formulate efficient queries, a mechanism is needed to automatically alert users regarding potentially interesting information contained within the collection. This paper presents the results of an experiment designed to test one approach to generation of such alerts. The technique of latent semantic indexing (LSI) is used to identify relationships among entities of interest. Entity extraction software is used to pre-process the text of the collection so that the LSI space contains representation vectors for named entities in addition to those for individual terms. In the LSI space, the cosine of the angle between the representation vectors for two entities captures important information regarding the degree of association of those two entities. For appropriate choices of entities, determining the entity pairs with the highest mutual cosine values yields valuable information regarding the contents of the text collection. The test database used for the experiment consists of 150,000 news articles. The proposed approach for alert generation is tested using a counterterrorism analysis example. The approach is shown to have significant potential for aiding users in rapidly focusing on information of potential importance in large text collections. The approach also has value in identifying possible use of aliases.
    Source
    Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  9. ALA / Subcommittee on Subject Relationships/Reference Structures: Final Report to the ALCTS/CCS Subject Analysis Committee (1997) 0.01 
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    Abstract
    The SAC Subcommittee on Subject Relationships/Reference Structures was authorized at the 1995 Midwinter Meeting and appointed shortly before Annual Conference. Its creation was one result of a discussion of how (and why) to promote the display and use of broader-term subject heading references, and its charge reads as follows: To investigate: (1) the kinds of relationships that exist between subjects, the display of which are likely to be useful to catalog users; (2) how these relationships are or could be recorded in authorities and classification formats; (3) options for how these relationships should be presented to users of online and print catalogs, indexes, lists, etc. By the summer 1996 Annual Conference, make some recommendations to SAC about how to disseminate the information and/or implement changes. At that time assess the need for additional time to investigate these issues. The Subcommittee's work on each of the imperatives in the charge was summarized in a report issued at the 1996 Annual Conference (Appendix A). Highlights of this work included the development of a taxonomy of 165 subject relationships; a demonstration that, using existing MARC coding, catalog systems could be programmed to generate references they do not currently support; and an examination of reference displays in several CD-ROM database products. Since that time, work has continued on identifying term relationships and display options; on tracking research, discussion, and implementation of subject relationships in information systems; and on compiling a list of further research needs.
    Content
    Enthält: Appendix A: Subcommittee on Subject Relationships/Reference Structures - REPORT TO THE ALCTS/CCS SUBJECT ANALYSIS COMMITTEE - July 1996 Appendix B (part 1): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (alphabetical display) (Separat in: http://web2.ala.org/ala/alctscontent/CCS/committees/subjectanalysis/subjectrelations/msrscu2.pdf) Appendix B (part 2): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (hierarchical display) Appendix C: Checklist of Candidate Subject Relationships for Information Retrieval. Compiled by Dee Michel, Pat Kuhr, and Jane Greenberg; edited by Greg Wool - June 1997 Appendix D: Review of Reference Displays in Selected CD-ROM Abstracts and Indexes by Harriette Hemmasi and Steven Riel Appendix E: Analysis of Relationships in Six LC Subject Authority Records by Harriette Hemmasi and Gary Strawn Appendix F: Report of a Preliminary Survey of Subject Referencing in OPACs by Gregory Wool Appendix G: LC Subject Referencing in OPACs--Why Bother? by Gregory Wool Appendix H: Research Needs on Subject Relationships and Reference Structures in Information Access compiled by Jane Greenberg and Steven Riel with contributions from Dee Michel and others edited by Gregory Wool Appendix I: Bibliography on Subject Relationships compiled mostly by Dee Michel with additional contributions from Jane Greenberg, Steven Riel, and Gregory Wool
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Konzeption und Anwendung des Prinzips Thesaurus
  10. Hoang, H.H.; Tjoa, A.M: ¬The state of the art of ontology-based query systems : a comparison of existing approaches (2006) 0.00 
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    Abstract
    Based on an in-depth analysis of existing approaches in building ontology-based query systems we discuss and compare the methods, approaches to be used in current query systems using Ontology or the Semantic Web techniques. This paper identifies various relevant research directions in ontology-based querying research. Based on the results of our investigation we summarise the state of the art ontology-based query/search and name areas of further research activities.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. Celik, I.; Abel, F.; Siehndel, P.: Adaptive faceted search on Twitter (2011) 0.00 
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    Abstract
    In the last few years, Twitter has become a powerful tool for publishing and discussing information. Yet, content exploration in Twitter requires substantial efforts and users often have to scan information streams by hand. In this paper, we approach this problem by means of faceted search. We propose strategies for inferring facets and facet values on Twitter by enriching the semantics of individual Twitter messages and present di erent methods, including personalized and context-adaptive methods, for making faceted search on Twitter more effective.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  12. Surfing versus Drilling for knowledge in science : When should you use your computer? When should you use your brain? (2018) 0.00 
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    Abstract
    For this second Special Issue of Infozine, we have invited students, teachers, researchers, and software developers to share their opinions about one or the other aspect of this broad topic: how to balance drilling (for depth) vs. surfing (for breadth) in scientific learning, teaching, research, and software design - and how the modern digital-liberal system affects our ability to strike this balance. This special issue is meant to provide a wide and unbiased spectrum of possible viewpoints on the topic, helping readers to define lucidly their own position and information use behavior.
    Content
    Editorial: Surfing versus Drilling for Knowledge in Science: When should you use your computer? When should you use your brain? Blaise Pascal: Les deux infinis - The two infinities / Philippe Hünenberger and Oliver Renn - "Surfing" vs. "drilling" in the modern scientific world / Antonio Loprieno - Of millimeter paper and machine learning / Philippe Hünenberger - From one to many, from breadth to depth - industrializing research / Janne Soetbeer - "Deep drilling" requires "surfing" / Gerd Folkers and Laura Folkers - Surfing vs. drilling in science: A delicate balance / Alzbeta Kubincová - Digital trends in academia - for the sake of critical thinking or comfort? / Leif-Thore Deck - I diagnose, therefore I am a Doctor? Will drilling computer software replace human doctors in the future? / Yi Zheng - Surfing versus drilling in fundamental research / Wilfred van Gunsteren - Using brain vs. brute force in computational studies of biological systems / Arieh Warshel - Laboratory literature boards in the digital age / Jeffrey Bode - Research strategies in computational chemistry / Sereina Riniker - Surfing on the hype waves or drilling deep for knowledge? A perspective from industry / Nadine Schneider and Nikolaus Stiefl - The use and purpose of articles and scientists / Philip Mark Lund - Can you look at papers like artwork? / Oliver Renn - Dynamite fishing in the data swamp / Frank Perabo 34 Streetlights, augmented intelligence, and information discovery / Jeffrey Saffer and Vicki Burnett - "Yes Dave. Happy to do that for you." Why AI, machine learning, and blockchain will lead to deeper "drilling" / Michiel Kolman and Sjors de Heuvel - Trends in scientific document search ( Stefan Geißler - Power tools for text mining / Jane Reed 42 Publishing and patenting: Navigating the differences to ensure search success / Paul Peters
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  13. Landauer, T.K.; Foltz, P.W.; Laham, D.: ¬An introduction to Latent Semantic Analysis (1998) 0.00 
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    Abstract
    Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word-word and passage-word lexical priming data; and as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  14. Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018) 0.00 
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    Abstract
    A challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academic and industry. To address this challenge, semantic analysis of textual data is focused in this paper. We propose an ontology-based approach to extract semantics of textual data and define the domain of data. In other words, we semantically analyse the social data at two levels i.e. the entity level and the domain level. We have chosen Twitter as a social channel challenge for a purpose of concept proof. Domain knowledge is captured in ontologies which are then used to enrich the semantics of tweets provided with specific semantic conceptual representation of entities that appear in the tweets. Case studies are used to demonstrate this approach. We experiment and evaluate our proposed approach with a public dataset collected from Twitter and from the politics domain. The ontology-based approach leverages entity extraction and concept mappings in terms of quantity and accuracy of concept identification.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  15. Oard, D.W.: Alternative approaches for cross-language text retrieval (1997) 0.00 
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    Abstract
    The explosive growth of the Internet and other sources of networked information have made automatic mediation of access to networked information sources an increasingly important problem. Much of this information is expressed as electronic text, and it is becoming practical to automatically convert some printed documents and recorded speech to electronic text as well. Thus, automated systems capable of detecting useful documents are finding widespread application. With even a small number of languages it can be inconvenient to issue the same query repeatedly in every language, so users who are able to read more than one language will likely prefer a multilingual text retrieval system over a collection of monolingual systems. And since reading ability in a language does not always imply fluent writing ability in that language, such users will likely find cross-language text retrieval particularly useful for languages in which they are less confident of their ability to express their information needs effectively. The use of such systems can be also be beneficial if the user is able to read only a single language. For example, when only a small portion of the document collection will ever be examined by the user, performing retrieval before translation can be significantly more economical than performing translation before retrieval. So when the application is sufficiently important to justify the time and effort required for translation, those costs can be minimized if an effective cross-language text retrieval system is available. Even when translation is not available, there are circumstances in which cross-language text retrieval could be useful to a monolingual user. For example, a researcher might find a paper published in an unfamiliar language useful if that paper contains references to works by the same author that are in the researcher's native language.
    Multilingual text retrieval can be defined as selection of useful documents from collections that may contain several languages (English, French, Chinese, etc.). This formulation allows for the possibility that individual documents might contain more than one language, a common occurrence in some applications. Both cross-language and within-language retrieval are included in this formulation, but it is the cross-language aspect of the problem which distinguishes multilingual text retrieval from its well studied monolingual counterpart. At the SIGIR 96 workshop on "Cross-Linguistic Information Retrieval" the participants discussed the proliferation of terminology being used to describe the field and settled on "Cross-Language" as the best single description of the salient aspect of the problem. "Multilingual" was felt to be too broad, since that term has also been used to describe systems able to perform within-language retrieval in more than one language but that lack any cross-language capability. "Cross-lingual" and "cross-linguistic" were felt to be equally good descriptions of the field, but "crosslanguage" was selected as the preferred term in the interest of standardization. Unfortunately, at about the same time the U.S. Defense Advanced Research Projects Agency (DARPA) introduced "translingual" as their preferred term, so we are still some distance from reaching consensus on this matter.
    I will not attempt to draw a sharp distinction between retrieval and filtering in this survey. Although my own work on adaptive cross-language text filtering has led me to make this distinction fairly carefully in other presentations (c.f., (Oard 1997b)), such an proach does little to help understand the fundamental techniques which have been applied or the results that have been obtained in this case. Since it is still common to view filtering (detection of useful documents in dynamic document streams) as a kind of retrieval, will simply adopt that perspective here.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010) 0.00 
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    Abstract
    Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.00 
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    Abstract
    We propose a method for improving access to scientific literature by analyzing the content of research papers beyond citation links and topic tracking. Our model relies on a typology of explicit semantic relations. These relations are instantiated in the abstract/introduction part of the papers and can be identified automatically using textual data and external ontologies. Preliminary results show a promising precision in unsupervised relationship classification.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. Neumann. M.: HAL: Hyperspace Analogue to Language (2012) 0.00 
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  19. Wang, Y.-H.; Jhuo, P.-S.: ¬A semantic faceted search with rule-based inference (2009) 0.00 
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    Abstract
    Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  20. Gnoli, C.; Pusterla, L.; Bendiscioli, A.; Recinella, C.: Classification for collections mapping and query expansion (2016) 0.00 
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    Abstract
    Dewey Decimal Classification has been used to organize materials owned by the three scientific libraries at the University of Pavia, and to allow integrated browsing in their union catalogue through SciGator, a home built web-based user interface. Classification acts as a bridge between collections located in different places and shelved according to different local schemes. Furthermore, cross-discipline relationships recorded in the system allow for expanded queries that increase recall. Advantages and possible improvements of such a system are discussed.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval

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