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Content

Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.

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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

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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.

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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.

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Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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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>

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Abstract

Bibliografische Daten, Normdaten und Metadaten im Semantic Web - Konzepte der Bibliografischen Kontrolle im Wandel. Der Titel dieser Arbeit zielt in ein essentielles Feld der Bibliotheks- und Informationswissenschaft, die Bibliografische Kontrolle. Als zweites zentrales Konzept wird der in der Weiterentwicklung des World Wide Webs (WWW) bedeutsame Begriff des Semantic Webs genannt. Auf den ersten Blick handelt es sich hier um einen ungleichen Wettstreit. Auf der einen Seite die Bibliografische Kontrolle, welche die Methoden und Mittel zur Erschließung von bibliothekarischen Objekten umfasst und traditionell in Form von formal-inhaltlichen Surrogaten in Katalogen daherkommt. Auf der anderen Seite das Buzzword Semantic Web mit seinen hochtrabenden Konnotationen eines durch Selbstreferenzialität "bedeutungstragenden", wenn nicht sogar "intelligenten" Webs. Wie kamen also eine wissenschaftliche Bibliothekarin und ein Mitglied des World Wide Web Consortiums 2007 dazu, gemeinsam einen Aufsatz zu publizieren und darin zu behaupten, das semantische Netz würde ein "bibliothekarischeres" Netz sein? Um sich dieser Frage zu nähern, soll zunächst kurz die historische Entwicklung der beiden Informationssphären Bibliothek und WWW gemeinsam betrachtet werden. Denn so oft - und völlig zurecht - die informationelle Revolution durch das Internet beschworen wird, so taucht auch immer wieder das Analogon einer weltweiten, virtuellen Bibliothek auf. Genauer gesagt, nahmen die theoretischen Überlegungen, die später zur Entwicklung des Internets führen sollten, ihren Ausgangspunkt (neben Kybernetik und entstehender Computertechnik) beim Konzept des Informationsspeichers Bibliothek.

Theme

Semantic Web

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Abstract

Integration externer Inhalte Inwieweit kann die Nutzung einer einheitlichen Terminologie zwischen Anfragesystem und Wissensbasis den Prozess der Informationsbeschaffung unterstützen? Zu diesem Zweck wird in einer ersten Phase ermittelt welche Wissensbasen aus der medizinischen Domäne in der Linked Data Cloud zur Verfügung stehen. Aufbauend auf den Ergebnissen werden Informationen aus verschiedenen dezentralen Wissensbasen exemplarisch integriert. Der Fokus der Betrachtung liegt dabei auf der verwendeten Terminologie sowie der Nutzung von Semantic Web Technologien. Neben Informationen aus der Linked Data Cloud erfolgt eine Suche nach medizinischer Literatur in PubMed. Wie auch in der Linked Data Cloud erfolgt die Integration unter Verwendung einer einheitlichen Terminologie. Eine weitere Fragestellung ist, wie Informationen aus insgesamt 21. Mio Aufsatzzitaten in PubMed sinnvoll integriert werden können. Dabei wird ermittelt welche Mechanismen eingesetzt werden können um die Präzision der Ergebnisse zu optimieren. Eignung medizinischer Begriffssystem Welche medizinischen Begriffssysteme existieren und wie eignen sich diese als zugrungeliegendes Vokabular für die automatische Verschlagwortung und Integration semantischer Inhalte? Der Fokus liegt dabei speziell auf einer Bewertung der Reichhaltigkeit von Begriffssystemen, wobei insbesondere der Detaillierungsgrad von Interesse ist. Handelt es sich um ein spezifisches oder allgemeines Begriffssystem und eignet sich dieses auch dafür bestimmte Teilaspekte der Medizin, wie bspw. die Chirurige oder die Anästhesie, in einer ausreichenden Tiefe zu beschreiben?

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Abstract

Die Arbeit befasst sich mit der Realisierung und der Durchführung einer automatischen DDCKlassifizierung durch das Indexierungssystem Lingo. Dies geschieht durch die Einbeziehung von Relationen des DFG-Projektes CrissCross, anhand derer Lingo bibliographische Titeldatensätze automatisch klassifiziert. Der dabei verwendete Ansatz wird mit dem üblichen methodischen Vorgehen bei automatischen Klassifizierungssystemen verglichen. Das Klassifizierungsverfahren wird daraufhin anhand einer Testkollektion von bibliographischen Titeldatensätzen der Deutschen Nationalbibliothek (DNB) getestet. Es folgt eine Diskussion der Ergebnisse und eine Bewertung des Klassifizierungssystems.

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Abstract

Die Bewertung der Indexierungsqualität bzw. -güte ist ein grundlegendes Problem von manuellen und automatischen Indexierungsverfahren. Letztere werden aber gerade im digitalen Zeitalter als einzige Möglichkeit angesehen, den zunehmenden Schwierigkeiten bibliothekarischer Informationsstrukturierung gerecht zu werden. Diese Arbeit befasst sich mit der Funktionsweise, Implementierung und Evaluierung der Sacherschließungssoftware MindServer Categorizer, der Firma Recommind, an der Deutschen Zentralbibliothek für Wirtschaftswissenschaften (ZBW). Grundlage der maschinellen Sacherschließung und anschließenden quantitativen und qualitativen Auswertung bilden rund 39.000 wirtschaftswissenschaftliche Dokumente aus den Datenbanken Econis und EconStor. Unter Zuhilfenahme des rund 6.000 Deskriptoren umfassenden Standard-Thesaurus Wirtschaft (STW) wird der ursprünglich rein statistische Indexierungsansatz des MindServer Categorizer zu einem begriffsorientierten Verfahren weiterentwickelt und zur Inhaltserschließung digitaler Informationsressourcen eingesetzt. Der zentrale Fokus dieser Arbeit liegt vor allem auf der Evaluierung der maschinell beschlagworteten Titel, in Anlehnung und entsprechender Anpassung der von Stock (2008) und Lancaster (2003) hierzu vorgeschlagenen Kriterien: Indexierungskonsistenz, -tiefe, -breite, -spezifität, -effektivität. Zusätzlich wird die Belegungsbilanz des STW evaluiert und es erfolgt ferner eine stichprobenartige, qualitative Bewertung der Ergebnisse seitens der zuständigen Fachreferenten und -referentinnen.

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Content

Bachelorarbeit, angefertigt im Studiengang B.A. Bildungswissenschaft an der FernUniversität in Hagen - Fakultät Kultur- und Sozialwissenschaften - Institut für Bildungswissenschaft und Medienforschung Lehrgebiet Bildungstheorie und Medienpädagogik. Vgl.: https://lesen-schreiben-bilden.net/wp-content/uploads/2017/02/BA_BB_ohnePr%C3%A4si_public.pdf.

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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.

Theme

Semantic Web

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Abstract

Gegenstand dieser Arbeit ist die Entwicklung eines funktionalen Prototyps einer Webanwendung für die Verknüpfung der Evaluierung von explorativen Suchen in Verbindung mit der Durchführung klassisches Retrievaltests. Als Grundlage für die Programmierung des Prototyps werden benutzerorientierte und systemorientierte Evalulierungsmethoden für Suchmaschinen analysiert und in einem theoretischen Modell zur Untersuchung von Informationssysteme und Suchmaschinen kombiniert. Bei der Gestaltung des Modells und des Prototyps wird gezeigt, wie sich aufgezeichnete Aktionsdaten praktisch für die Suchmaschinenevaluierung verwenden lassen, um auf der einen Seite eine Datengrundlage für Retrievaltests zu gewinnen und andererseits, um für die Auswertung von Relevanzbewertungen auch das implizierte Feedback durch Handlungen der Anwender zu berücksichtigen. Retrievaltests sind das gängige und erprobte Mittel zur Messung der Retrievaleffektiviät von Informationssystemen und Suchmaschinen, verzichten aber auf eine Berücksichtigung des tatsächlichen Nutzerverhaltens. Eine Methode für die Erfassung der Interaktionen von Suchmaschinennutzern sind protokollbasierte Tests, mit denen sich Logdateien über Benutzer einer Anwendung generieren lassen. Die im Rahmen der Arbeit umgesetzte Software bietet einen Ansatz, Retrievaltests auf Basis protokollierter Nutzerdaten in Verbindung mit kontrollierten Suchaufgaben, durchzuführen. Das Ergebnis dieser Arbeit ist ein fertiger funktionaler Prototyp, der in seinem Umfang bereits innerhalb von Suchmaschinenstudien nutzbar ist.

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Abstract

Die Arbeit analysiert die dynamische Entwicklung und den Gebrauch von Thesaurusbegriffen. Zusätzlich konzentriert sie sich auf die Faktoren, die die Zahl von Indexbegriffen pro Dokument oder Zeitschrift beeinflussen. Als Untersuchungsobjekt dienten der MeSH und die entsprechende Datenbank "MEDLINE". Die wichtigsten Konsequenzen sind: 1. Der MeSH-Thesaurus hat sich durch drei unterschiedliche Phasen jeweils logarithmisch entwickelt. Solch einen Thesaurus sollte folgenden Gleichung folgen: "T = 3.076,6 Ln (d) - 22.695 + 0,0039d" (T = Begriffe, Ln = natürlicher Logarithmus und d = Dokumente). Um solch einen Thesaurus zu konstruieren, muss man demnach etwa 1.600 Dokumente von unterschiedlichen Themen des Bereiches des Thesaurus haben. Die dynamische Entwicklung von Thesauri wie MeSH erfordert die Einführung eines neuen Begriffs pro Indexierung von 256 neuen Dokumenten. 2. Die Verteilung der Thesaurusbegriffe erbrachte drei Kategorien: starke, normale und selten verwendete Headings. Die letzte Gruppe ist in einer Testphase, während in der ersten und zweiten Kategorie die neu hinzukommenden Deskriptoren zu einem Thesauruswachstum führen. 3. Es gibt ein logarithmisches Verhältnis zwischen der Zahl von Index-Begriffen pro Aufsatz und dessen Seitenzahl für die Artikeln zwischen einer und einundzwanzig Seiten. 4. Zeitschriftenaufsätze, die in MEDLINE mit Abstracts erscheinen erhalten fast zwei Deskriptoren mehr. 5. Die Findablity der nicht-englisch sprachigen Dokumente in MEDLINE ist geringer als die englische Dokumente. 6. Aufsätze der Zeitschriften mit einem Impact Factor 0 bis fünfzehn erhalten nicht mehr Indexbegriffe als die der anderen von MEDINE erfassten Zeitschriften. 7. In einem Indexierungssystem haben unterschiedliche Zeitschriften mehr oder weniger Gewicht in ihrem Findability. Die Verteilung der Indexbegriffe pro Seite hat gezeigt, dass es bei MEDLINE drei Kategorien der Publikationen gibt. Außerdem gibt es wenige stark bevorzugten Zeitschriften."

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Abstract

Ziel: Ziel dieser Bachelorarbeit war es, die Übertragbarkeit der allgemeinen Rankingfaktoren, wie sie von Web-Suchmaschinen verwendet werden, auf Discovery-Systeme zu analysieren. Dadurch könnte das bisher hauptsächlich auf dem textuellen Abgleich zwischen Suchanfrage und Dokumenten basierende bibliothekarische Ranking verbessert werden. Methode: Hierfür wurden Faktoren aus den Gruppen Popularität, Aktualität, Lokalität, Technische Faktoren, sowie dem personalisierten Ranking diskutiert. Die entsprechenden Rankingfaktoren wurden nach ihrer Vorkommenshäufigkeit in der analysierten Literatur und der daraus abgeleiteten Wichtigkeit, ausgewählt. Ergebnis: Von den 23 untersuchten Rankingfaktoren sind 14 (61 %) direkt vom Ranking der Web-Suchmaschinen auf das Ranking der Discovery-Systeme übertragbar. Zu diesen zählen unter anderem das Klickverhalten, das Erstellungsdatum, der Nutzerstandort, sowie die Sprache. Sechs (26%) der untersuchten Faktoren sind dagegen nicht übertragbar (z.B. Aktualisierungsfrequenz und Ladegeschwindigkeit). Die Linktopologie, die Nutzungshäufigkeit, sowie die Aktualisierungsfrequenz sind mit entsprechenden Modifikationen übertragbar.

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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.

Theme

Semantic Web

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Date

11. 9.2012 19:43:22

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Abstract

Das Wissensmanagement ist ein Themenkomplex mit zahlreichen fachlichen Bezügen, insbesondere zur Wirtschaftsinformatik und der Management-, Personal- und Organisationslehre als Teilbereiche der Betriebswirtschaftslehre. In einem weiter gefassten Verständnis bestehen aber auch Bezüge zur Organisationspsychologie, zur Informatik und zur Informationswissenschaft. Von den Entwicklungen in diesen Bezugsdisziplinen können deshalb auch Impulse für die Konzepte, Methodiken und Technologien des Wissensmanagements ausgehen. Die aus der Informatik stammende Idee, das World Wide Web (WWW) zu einem semantischen Netz auszubauen, kann als eine solche impulsgebende Entwicklung gesehen werden. Im Verlauf der vergangenen Dekade hat diese Idee einen hinreichenden Reifegrad erreicht, so dass eine potenzielle Relevanz auch für das Wissensmanagement unterstellt werden darf. Im Rahmen dieser Arbeit soll anhand eines konkreten, konzeptionellen Ansatzes demonstriert werden, wie dieser technologische Impuls für das Wissensmanagement nutzenbringend kanalisiert werden kann. Ein derartiges Erkenntnisinteresse erfordert zunächst die Erarbeitung eines operationalen Verständnisses von Wissensmanagement, auf dem die weiteren Betrachtungen aufbauen können. Es werden außerdem die Architektur und die Funktionsweise eines "Semantic Web" sowie XML und die Ontologiesprachen RDF/RDFS und OWL als maßgebliche Werkzeuge für eine ontologiebasierte Wissensrepräsentation eingeführt. Anschließend wird zur Integration und Anwendung dieser semantischen Technologien in das Wissensmanagement ein Ansatz vorgestellt, der eine weitgehend automatisierte Wissensmodellierung und daran anschließende, semantische Informationserschließung der betrieblichen Datenbasis beschreibt. Zur Veranschaulichung wird dazu auf eine fiktive Beispielwelt aus der Fertigungsindustrie zurückgegriffen. Schließlich soll der Nutzen dieser Vorgehensweise durch Anwendungsszenarien des Information Retrieval (IR) im Kontext von Geschäftsprozessen illustriert werden.