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Author, Editor

Author(s):

Elbassuoni, Shady
Hose, Katja
Metzger, Steffen
Schenkel, Ralf

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Not MPG Author(s):

Schenkel, Ralf

Editor(s):





BibTeX cite key*:

ROXXI_VLDB2010

Title, Booktitle

Title*:

ROXXI: Reviving witness dOcuments to eXplore eXtracted Information

Booktitle*:

Proceedings of the 36th International Conference on Very Large Data Bases

Event, URLs

URL of the conference:


URL for downloading the paper:

http://www.comp.nus.edu.sg/~vldb2010/proceedings/files/papers/D19.pdf

Event Address*:

Singapore

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

9 April 2010

Event End Date:

9 April 2010

Publisher

Name*:

ACM

URL:


Address*:

New York, NY

Type:


Vol, No, Year, pp.

Series:

Proceedings of the VLDB Endowment

Volume:

3

Number:

1-2

Month:


Pages:

1589-1592

Year*:

2010

VG Wort Pages:


ISBN/ISSN:


Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

In recent years, there has been considerable research on information
extraction and constructing RDF knowledge bases. In general,
the goal is to extract all relevant information from a corpus of documents,
store it into an ontology, and answer future queries based
only on the created knowledge base. Thus, the original documents
become dispensable. On the one hand, an ontology is a convenient
and non-redundant structured source of information, based
on which specific queries can be answered efficiently. On the other
hand, many users doubt the correctness of facts and ontology subgraphs
presented to them as query results without proof. Instead,
users often wish to verify the obtained facts or subgraphs by reading
about them in context, i.e., in a document relating the facts
and providing background information. In this demo, we present
ROXXI, a system operating on top of an existing knowledge base
and reviving the abandoned witness documents. In doing so, it goes
the opposite way of information extraction approaches – starting
with ontological facts and tracing their way back to the documents
they were extracted from. ROXXI offers interfaces for expert users
(SPARQL) as well as for non-experts (ontology browser) and provides
a ranked list of documents each associated with a content
snippet highlighting the queried facts in context. At the demonstration
site, we will show the advantages of this novel approach
towards document retrieval and illustrate the benefits of reviving
the documents that information extraction approaches neglect.

HyperLinks / References / URLs:

http://portal.acm.org/citation.cfm?id=1920841.1921046



Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Research Context:

WisNetGrid

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{ROXXI_VLDB2010,
AUTHOR = {Elbassuoni, Shady and Hose, Katja and Metzger, Steffen and Schenkel, Ralf},
TITLE = {ROXXI: {Reviving} witness {dOcuments} to {eXplore} {eXtracted} {Information}},
BOOKTITLE = {Proceedings of the 36th International Conference on Very Large Data Bases},
JOURNAL = {Proceedings of the VLDB Endowment},
PUBLISHER = {ACM},
YEAR = {2010},
NUMBER = {1-2},
VOLUME = {3},
PAGES = {1589--1592},
SERIES = {Proceedings of the VLDB Endowment},
ADDRESS = {Singapore},
ISBN = {2150-8097},
}


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Created
06/12/2010 06:17:54 PM
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