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Author, Editor

Author(s):

Kasneci, Gjergji
Suchanek, Fabian
Ifrim, Georgiana
Elbassuoni, Shady
Ramanath, Maya
Weikum, Gerhard

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Editor(s):

Tsong-Li Wang, Jason

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BibTeX cite key*:

Kasneci@sigmod2008

Title, Booktitle

Title*:

NAGA: Harvesting, Searching and Ranking Knowledge (demo)

Booktitle*:

Proceedings of the ACM SIGMOD 2008 International Conference on Management of Data (SIGMOD 2008)

Event, URLs

URL of the conference:

http://www.sigmod08.org/

URL for downloading the paper:

http://portal.acm.org/ft_gateway.cfm?id=1376756&type=pdf&coll=GUIDE&dl=GUIDE&CFID=11411533&CFTOKEN=27279737

Event Address*:

Vancouver, Canada 2008

Language:

English

Event Date*
(no longer used):


Organization:

ACM

Event Start Date:

10 June 2008

Event End Date:

12 June 2008

Publisher

Name*:

ACM

URL:

http://www.acm.org

Address*:

New York, NY, USA

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:

June

Pages:

1285-1288

Year*:

2008

VG Wort Pages:


ISBN/ISSN:

978-1-60558-102-6

Sequence Number:


DOI:

http://doi.acm.org/10.1145/1376616.1376756



Note, Abstract, ©


(LaTeX) Abstract:

The presence of encyclopedic Web sources, such as Wikipedia, the Internet Movie Database (IMDB), World Factbook, etc. calls for new querying techniques that are simple and yet more expressive than those provided by standard keyword-based search engines. Searching for explicit knowledge needs to consider inherent semantic structures involving entities and relationships.

In this demonstration proposal, we describe a semantic search system named NAGA. NAGA operates on a knowledge graph, which contains millions of entities and relationships derived from various encyclopedic Web sources, such as the ones above. NAGA's graph-based query language is geared towards expressing queries with additional semantic information. Its scoring model is based on the principles of generative language models, and formalizes several desiderata such as confidence, informativeness and compactness of answers.

We propose a demonstration of NAGA which will allow users to browse the knowledge base through a user interface, enter queries in NAGA's query language and tune the ranking parameters to test various ranking aspects.

URL for the Abstract:

http://portal.acm.org/citation.cfm?doid=1376616.1376756

Keywords:

Algorithms, Design, Experimentation



Download
Access Level:

Internal

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Audience:

popular

Appearance:

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



BibTeX Entry:

@INPROCEEDINGS{Kasneci@sigmod2008,
AUTHOR = {Kasneci, Gjergji and Suchanek, Fabian and Ifrim, Georgiana and Elbassuoni, Shady and Ramanath, Maya and Weikum, Gerhard},
EDITOR = {Tsong-Li Wang, Jason},
TITLE = {{NAGA}: Harvesting, Searching and Ranking Knowledge (demo)},
BOOKTITLE = {Proceedings of the ACM SIGMOD 2008 International Conference on Management of Data (SIGMOD 2008)},
PUBLISHER = {ACM},
YEAR = {2008},
ORGANIZATION = {ACM},
PAGES = {1285--1288},
ADDRESS = {Vancouver, Canada 2008},
MONTH = {June},
ISBN = {978-1-60558-102-6},
DOI = {http://doi.acm.org/10.1145/1376616.1376756},
}


Entry last modified by Martin Theobald, 04/23/2009
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Editor(s)
Gjergji Kasneci
Created
10/10/2008 11:20:55 AM
Revisions
5.
4.
3.
2.
1.
Editor(s)
Martin Theobald
Martin Theobald
Fabian Suchanek
Olha Condor
Olha Condor
Edit Dates
04/23/2009 03:04:49 PM
04/14/2009 02:45:37 PM
11/18/2008 03:19:05 PM
18.11.2008 13:03:34
18.11.2008 12:22:05