Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Classification and Intelligent Search on Information in XML

Fuhr, N., & Weikum, G. (2002). Classification and Intelligent Search on Information in XML. IEEE Data Engineering Bulletin, 25(1), 51-58.

Item is

Dateien

einblenden: Dateien
ausblenden: Dateien
:
fuhrW02.pdf (beliebiger Volltext), 48KB
 
Datei-Permalink:
-
Name:
fuhrW02.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Privat
MIME-Typ / Prüfsumme:
application/pdf
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-
Lizenz:
-

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Fuhr, Norbert, Autor
Weikum, Gerhard1, Autor           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: {XML} will be the method of choice for representing all kinds of documents in product catalogs, digital libraries, scientific data repositories, and across the Web. This observation creates high expectations that {XML} will be a major catalyst in constructing the “Semantic Web”. However, merely casting all documents into {XML} format does not necessarily make a document’s semantics explicit and more amenable for effective information searching. Rather, to fully leverage {XML} on a global scale, significant progress is needed on the following issues: 1. providing an easy-to-use yet powerful and efficient search language that combines concepts from current {XML} pattern-matching languages (e.g., {XP}ath, {XQ}uery, etc.) with ontology-backed information-retrievalstyle search result ranking, 2. extracting more semantics from existing document collections by constructing structural and ontological skeletons (e.g., in the form of {DTD}s or {XML} schemas) that describe the data at a higher semantic level and can also facilitate new forms of indexing for efficiency, and 3. classifying existing documents according to a given thematic or personalized, hierarchical ontology to make searching more effective (e.g., exploit relevance feedback) and efficient (e.g., limit the search focus). {CLASSIX}, a joint project of the Universities of Dortmund and the Saarland in Germany, addresses these three issues. We describe our approaches for each of these topics in the remainder of this paper.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2007-04-132002
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: eDoc: 520372
Anderer: Local-ID: C1256DBF005F876D-49001CE30715F797C12572BC00404DAC-FuhrW02
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: IEEE Data Engineering Bulletin
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 25 (1) Artikelnummer: - Start- / Endseite: 51 - 58 Identifikator: -