9.864, Calls: Lang Processing,Multimedia Indexing & Retrieval
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Wed Jun 10 14:42:28 UTC 1998
LINGUIST List: Vol-9-864. Wed Jun 10 1998. ISSN: 1068-4875.
Subject: 9.864, Calls: Lang Processing,Multimedia Indexing & Retrieval
Moderators: Anthony Rodrigues Aristar: Texas A&M U. <aristar at linguistlist.org>
Helen Dry: Eastern Michigan U. <hdry at linguistlist.org>
Review Editor: Andrew Carnie <carnie at linguistlist.org>
Editors: Brett Churchill <brett at linguistlist.org>
Martin Jacobsen <marty at linguistlist.org>
Elaine Halleck <elaine at linguistlist.org>
Anita Huang <anita at linguistlist.org>
Ljuba Veselinova <ljuba at linguistlist.org>
Julie Wilson <julie at linguistlist.org>
Software development: John H. Remmers <remmers at emunix.emich.edu>
Zhiping Zheng <zzheng at online.emich.edu>
Home Page: http://linguistlist.org/
Editor for this issue: Anita Huang <anita at linguistlist.org>
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1)
Date: Mon, 8 Jun 1998 17:42:42 +0200 (MET DST)
From: Walter.Daelemans at kub.nl
Subject: Special Issue JETAI
2)
Date: Mon, 8 Jun 1998 16:55:29 -0400 (EDT)
From: Zhongfei Zhang <zhongfei at cedar.buffalo.edu>
Subject: ACM SIGIR98 Workshop on Multimedia Indexing and Retrieval
-------------------------------- Message 1 -------------------------------
Date: Mon, 8 Jun 1998 17:42:42 +0200 (MET DST)
From: Walter.Daelemans at kub.nl
Subject: Special Issue JETAI
CALL FOR PAPERS
JOURNAL OF EXPERIMENTAL AND THEORETICAL ARTIFICIAL INTELLIGENCE
Special Issue on
MEMORY-BASED LANGUAGE PROCESSING
Memory-Based Language Processing (MBLP) views language processing as
being based on the direct reuse of previous experience rather than on
the use of abstractions extracted from that experience. In such a
framework, language acquisition is modeled as the storage of
exemplars, and language processing as similarity-based reasoning.
MBLP derives from work in Artificial Intelligence (case-based
reasoning, memory-based reasoning, instance-based learning, lazy
learning), Linguistics (analogical modeling), Computational
Linguistics (example-based machine translation, case-based language
processing, data-oriented parsing), and Statistical Pattern
Recognition (k-nn models). In recent research, it has been shown that
the application of algorithms based on this framework leads to
accurate and efficient language models in diverse language processing
areas (phonology, morphology, syntax, semantics, discourse).
We invite theoretical papers on models, algorithms and metrics for
memory-based language processing, and empirical studies comparing MBLP
variants to each other or to alternative non-memory-based approaches
for specific language processing tasks.
Time Table
Deadline for submissions: September 1, 1998
Notification Date: November 1, 1998
Deadline for final versions: January 1, 1999
Special Issue: Summer or Autumn 1999
Instructions for Authors:
1. The original manuscript and three clear copies should be submitted
to:
Walter Daelemans (guest editor)
ILK Research Group, Computational Linguistics
Tilburg University
Warandelaan 2
5037 GC Tilburg
Building B, Room 307
The Netherlands
+31 13 4663070 (Phone)
+31 13 4663110 (Fax)
walter.daelemans at kub.nl
All papers will be refereed by at least three reviewers.
2. All papers must be in English. The entire manuscript should be
typed on one side only of plain paper, either A4 or 8.5 x 11 inch,
with double spacing used throughout.
3. The first page of the manuscript should carry the title, the names,
institutional addresses, and institutional telephone numbers of the
authors, and a short title of no more than 50 characters (including
spaces) to be used as a running head. The second page of the
manuscript should carry an abstract of about 200 words. The remainder
of the text should not exceed 30 double spaced pages, including
references but excluding figures and tables. All figures and tables
must be referred to by number in the text.
4. An original set of professional quality figures should accompany
the manuscript. Line drawing may be India ink originals or glossy
prints. Halftone illustrations must be submitted as glossy
prints. Illustrations cannot be printed in color.
5. Tables should be typed on separate pages, which should accompany
the text.
6. The text should be written in third person to facilitate blind
reviewing. The names of the authors or their institutions should
appear only on the title page.
7. The name-date style should be used for all references. All authors'
names should be included in the reference list. Journal names should
not be abbreviated. Inclusive page numbers must be given for all
references to articles in journals, proceedings volumes, or
books. With the exception of theses or dissertations, unpublished
works should not be included as references.
8. Footnotes may not be used. Endnotes may be used if necessary; they
should be collected on separate sheets at the end of the text.
9. Fifty free offprints will be provided to the first author of each
paper. There will be no page charges.
-------------------------------- Message 2 -------------------------------
Date: Mon, 8 Jun 1998 16:55:29 -0400 (EDT)
From: Zhongfei Zhang <zhongfei at cedar.buffalo.edu>
Subject: ACM SIGIR98 Workshop on Multimedia Indexing and Retrieval
****************************************************************************
NOTE THAT THE DEADLINE FOR INITIAL SUBMISSION HAS BEEN EXTENDED TO JUNE 19
****************************************************************************
ACM SIGIR'98 Post-Conference Workshop
MULTIMEDIA INDEXING AND RETRIEVAL
Melbourne, Australia, August 28, 1998
Call for Participation
Background:
This workshop will focus on the required functionality, techniques, and
evaluation criteria for multimedia information retrieval systems.
Researchers have been investigating content-based retrieval
from non-text sources such as images, audio and video. Initially, the
focus of these efforts were on content analysis and retrieval
techniques tailored to a specific
media; more recently, researchers have started to combine attributes
from various media.
The goal of multimedia IR systems is to handle general
queries such as "find outdoor pictures or video of Clinton and Gore discussing
environmental issues". Answering such queries requires intelligent
exploitation of both text/speech and visual content. Multimedia
IR is a very broad area covering both infrastructure issues (e.g.
efficient storage criteria, networking, client-server models) and
intelligent content analysis and retrieval. Since this is a one-day workshop,
we have chosen three focus areas in the intelligent analysis and retrieval
area.
About the Workshop:
The first focus of this workshop is on integrating
information from various media sources in order to handle multimodal
queries on large, diverse databases. An example of such a collection
would be the WWW. In such cases, a query may be decomposed into a
set of media queries, each involving a different indexing scheme.
The interaction of various media sources that occur in the same
context (e.g., text accompanying pictures, audio accompanying video)
is of special interest; such interaction can be exploited in both the
content analysis and retrieval phases.
The second focus deals with examples of research using content and organization
of multimedia information into semantic classes.
Users pose and expect a retrieval to provide answers
to semantic questions. In practice this is difficult to achieve. Building
structures that encode semantic information in a fairly domain independent
and robust manner is extremely difficult. A quick review of computer vision
research over the last few years points to this difficulty. In many cases,
image content can be used in conjunction with user interaction and domain
specificity to retrieve semantically meaningful information. However, it
is clear that retrieval by similarity of visual attributes when used
arbitrarily cannot provide semantically meaningful information. For example,
a search for a red flower by color red on a very heterogeneous database
cannot be expected to yeild meaningful results. On the other hand retrieval
of red flowers in a database of flowers can be achieved using color. In
context therefore, examples of research using content and organization
of multimedia information into semantic classes will
be discussed.
Many systems, particularly image and video based
ones require an example picture which can be used as a query (alternatively,
the user may be required to draw a picture). It may be unrealistic to expect
an example image to be always available. Thus, it would be useful to find
ways of generating new queries. Can NLP techniques be combined with computer
vision techniques to generate such queries? Or can multimodal retrieval
techniques be combined to create queries suitable for image, video and
audio retrieval? In general, a question is how can we create realistic
queries for realistic systems.
The third focus of this workshop is on evaluation techniques for
multimedia retrieval. Currently, most researchers are using the
standard evaluation measures defined for text documents; these need to
be extended/modified for multimedia documents. There is also a
high degree of subjectivity involved that needs to be addressed.
We will focus on the following specific topics:
- content analysis and retrieval from various media
(text, images, video, audio)
- interaction of modalities (e.g. text, images) in indexing, retrieval
- effective user interfaces (permitting query refinement etc.)
- evaluation methodologies for multimedia information. We have
found that researchers pay insufficient attention to it.
- techniques for relevance ranking
- multimodal query formation/decomposition
- logic formalisms for multimodal queries
- indexing and retrieval from scanned documents - e.g extracting text
from images, word spotting - as a retrieval technique for
both handwritten and printed documents.
- testbeds for evaluating multimodal retrieval: it would be nice to
have some resource sharing here since annotating these, and coming
up with a good query set are difficult
Participation:
Two types of participation are expected. Those interested in making a
presentation at this workshop should submit their full papers either in
online postscript version or in hardcopy by regular mail to the
address given below.
The papers should not exceed 5,000 words, including figures,
tables, and references. Those interested in participating, but not
presenting papers, should submit a statement of interest, not to exceed
500 words. This should clearly state what aspect(s) of the workshop
reflect their research interest. These will be used to select panelists.
Both types of submissions are due on
Friday, June 5th. Decisions
will be made no later than Friday, June 26th. In the case of paper submission,
the final camera-ready papers are due on July 24th.
Working notes will be made available to all participants at the workshop.
All the submissions should be sent to:
Prof. Rohini K. Srihari,
CEDAR/SUNY at Buffalo
UB Commons
520 Lee Entrance, Suite 202
Amherst, NY 14228 - 2583
rohini at cedar.buffalo.edu
Organization:
Workshop Chairs (also program chairs)
Rohini K. Srihari, SUNY at Buffalo (rohini at cedar.buffalo.edu)
Zhongfei Zhang, SUNY at Buffalo (zhongfei at cedar.buffalo.edu)
R. Manmatha, University of Massachussetts (manmatha at cs.umass.edu)
S. Ravela, University of Massachussetts (ravela at cs.umass.edu)
Program Committee Members:
Shih-Fu Chang (Columbia U., USA)
David Harper (Robert Gordon University, U. K.)
Alex Hauptmann (CMU, USA)
Rakesh Kumar (Sarnoff, USA)
Desai Narasimhalu (ISI, Singapore)
Candace Sidner (Lotus, USA)
Peter Schauble (ETH, Switzerland)
Timetable:
Paper or statement of interest submission: June 5th, 1998
Decision: July 19th, 1998
Camera-Ready Paper Due: July 24th, 1998
SIGIR Conference: August 24th - 28th, 1998
Workshop: August 29th, 1998
Further Information:
Further questions may be directed to the address above, or go to the
Web page of this workshop at http://www.cedar.buffalo.edu/sigir98/MMTR.html
or the SIGIR Conference main Web Page at http://www.cs.mu.oz.au/sigir98/
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