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Proceedings Article, Paper
@InProceedings
Beitrag in Tagungsband, Workshop

Author, Editor
Author(s):
Bast, Holger
Majumdar, Debapriyo		dblp
dblp
Editor(s):
Marchionini, Gary
Moffat, Alistair
Tait, John
Baeza-Yates, Ricardo
Ziviani, Nivio		dblp
dblp
dblp
dblp
dblp
Not MPII Editor(s):
Marchionini, Gary
Moffat, Alistair
Tait, John
Baeza-Yates, Ricardo
Ziviani, Nivio
BibTeX cite key*:
bastmajumdar05sigir
Title, Booktitle
Title*:
Why Spectral Retrieval Works
lsiexplained.pdf (175.82 KB)
Booktitle*:
28th Annual International Conference on Research and Development in Information Retrieval (SIGIR'05)
Event, URLs
Conference URL::
http://www.sigir2005.org/
Downloading URL:
Event Address*:
Salvador, Brazil
Language:
English
Event Date*
(no longer used):
Organization:
Event Start Date:
15 August 2005
Event End Date:
19 August 2005
Publisher
Name*:
ACM
URL:
Address*:
New York, USA
Type:
Vol, No, Year, pp.
Series:
Volume:
Number:
Month:
August
Pages:
11-18
Year*:
2005
VG Wort Pages:
ISBN/ISSN:
1-58113-881-4
Sequence Number:
DOI:
Note, Abstract, ©
(LaTeX) Abstract:
 We introduce the \emph{synonymy graph} as a new angle of looking at spectral
retrieval techniques, including latent semantic indexing (LSI) and its many
successors. The synonymy graph is defined for each pair of terms in the
collection, and our findings suggest that it is at the heart of what makes
spectral retrieval work in practice.
%
We show that LSI and many of its variants can be equivalently viewed as a
particular document expansion (not query expansion) process, where each term
effects the insertion of some other term if and only if the synonymy graph for
that term pair has a certain characteristic shape. We provide a simple,
parameterless algorithm for detecting that shape.
%
We point out inherent problems of every algorithm that bases its expansion
decisions merely on individual values of the synonymy graph, as done by almost
all existing methods. Our new algorithm overcomes these limitations, and it
consistently outperforms previous methods on a number of test collections.
%
Our synonymy graphs also shed light on the effectiveness of three fundamental
types of variations of the basic LSI scheme.
Keywords:
Spectral Retrieval, Latent Semantic Indexing, Document Expansion
Download
Access Level:
Public

Correlation
MPG Unit:
Max-Planck-Institut für Informatik
MPG Subunit:
Algorithms and Complexity 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{bastmajumdar05sigir,
AUTHOR = {Bast, Holger and Majumdar, Debapriyo},
 EDITOR = {Marchionini, Gary and Moffat, Alistair and Tait, John and Baeza-Yates, Ricardo and Ziviani, Nivio},
 TITLE = {Why Spectral Retrieval Works},
 BOOKTITLE = {28th Annual International Conference on Research and Development in Information Retrieval (SIGIR'05)},
 PUBLISHER = {ACM},
 YEAR = {2005},
 PAGES = {11--18},
 ADDRESS = {Salvador, Brazil},
 MONTH = {August},
 ISBN = {1-58113-881-4},
}

Entry last modified by Holger Bast, 09/17/2006
Hide details for Edit History (please click the blue arrow to see the details)Edit History (please click the blue arrow to see the details)

Editor(s)
Debapriyo Majumdar		Created
04/14/2005 13:28:22
Revisions
12.
11.
10.
9.
8.		Editor(s)
Holger Bast
Christine Kiesel
Christine Kiesel
Christine Kiesel
Christine Kiesel		Edit Dates
09/17/2006 01:45:44 AM
20.03.2006 14:56:56
20.03.2006 14:53:19
14.11.2005 14:25:40
08/22/2005 08:00:15 PM

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lsiexplained.pdf