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Subject:

Focused Retrieval and Result Aggregation, Journal of Information Retrieval-Special Issue

From:

Andrew Trotman <[log in to unmask]>

Reply-To:

Andrew Trotman <[log in to unmask]>

Date:

Thu, 4 Dec 2008 13:24:03 +1300

Content-Type:

text/plain

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Call for Papers
Journal of Information Retrieval Special Issue on
FOCUSED RETRIEVAL AND RESULT AGGREGATION

GUEST EDITORS
*Andrew Trotman ([log in to unmask]), University of Otago, New Zealand
*Mounia Lalmas ([log in to unmask]), University of Glasgow, UK
*Shlomo Geva ([log in to unmask]), Queensland University of Technology, 
Australia
*Jaap Kamps ([log in to unmask]), University of Amsterdam, The Netherlands
*Vanessa Murdock ([log in to unmask]), Yahoo! Research Barcelona, 
Spain

DETAILS
Standard document retrieval finds atomic documents.  It leaves to the user 
the tasks of locating relevant information within a document, and that of 
aggregating different results (each corresponding to a piece of the sought 
information) into a final answer. Focused retrieval addresses the first task 
by providing the user a more direct access to relevant information; result 
aggregation addresses the second task by a creating a single "result", an 
answer constructed from the relevant components (using summarization and 
presentation techniques).

FOCUSED RETRIEVAL aims to identify not only documents relevant to a user 
information need, but also where within the document the relevant 
information is located. It aims to satisfy the user information need and not 
to just identify documents that satisfy the information need.  There are 
three main forms of focused retrieval: element retrieval, passage retrieval, 
and question answering. Element Retrieval (also known as XML-IR) can be 
applied when the documents in the collection contain some kind of markup 
(such as XML). The retrieval engine will typically exploit the structure to 
identify the most relevant paragraphs, sections or documents to return as 
answers to a query. With passage retrieval, the retrieval engine will 
typically choose the appropriate size of results to return and the location 
based mostly on the content of the document (and sometimes its structure). 
Whereas element retrieval and passage retrieval are used for information 
seeking questions, question answering (QA) aims to answer more fact seeking 
questions, and makes use of natural language processing techniques.

Question answering has been investigated in TREC, CLEF and NCTIR for many 
years, and since 2008 in INEX, and is arguably the ultimate goal of semantic 
web search research for interrogative information needs. Passage retrieval 
has a long history in information retrieval research, including INEX and the 
TREC genomics track, but is also important when searching long documents of 
any kind. Element retrieval has been the core task at INEX, and is now being 
investigated in the INEX book search track.
The aim of element retrieval (XML-IR) is to identify the most relevant 
document components to return as an answer to the query. It has already been 
shown that returning several elements together as one answer triggers a 
stronger user satisfaction than returning a single element on its own. In 
the relevance in context retrieval task at INEX, the aim is to return 
documents constructed from their most relevant elements; the elements are 
aggregated to form one result. More generally, elements or passages from 
different documents might be selected to form an aggregated result.  In 
Yahoo! Alpha and Google Universal a query already yields results from a 
variety of different sources including: images, videos, news, and sponsored 
results; all aggregated into a single results page.

RESULT AGGREGATION is a form of automatic document construction. Given a set 
of documents and document components that satisfy a user's information need 
(perhaps identified using focused retrieval), an aggregator will combine 
these into a single result. Techniques include multiple-component 
summarization, meta-search like result presentation, and mixed-media 
presentation (when searching over heterogeneous collections of, for example, 
text, images, video, and music).
This special issue on Focused Retrieval and Result Aggregation intentionally 
covers two topics, but in particular we are interested in examining the 
entire search process from user query through to aggregated document 
presentation. The aim of this special issue is to present the current 
state-of-the-art and the most recent developments in focused retrieval, 
result aggregation, and their relationship. It also aims to offer a 
thoughtful perspective of the potential and emerging challenges of these two 
paradigms.

Prospective authors who aim to contribute to this special issue are 
encouraged to submit original and unpublished papers dealing with Focused 
Retrieval, Result Aggregation, or the combination of the two. Papers are 
solicited in any of (but not limited to) the following areas:

*Algorithmic approaches to focused retrieval and/or result aggregation
*Relationship between focused retrieval and result aggregation
*The effect of media, language and context
*Interface and presentation issues
*Evaluation, e.g. effectiveness, user-centered
*Applications, e.g. web search, mobile search, wiki search, wiki linking, 
etc
*Use cases, e.g. education, law, travel, etc

IMPORTANT DATES
Papers due: 1 May 2009
Review and revision completed: 1 July 2009
Camera ready paper due: 1 September 2009

SUBMISSION
The guidelines for authors and reviewers are available for download from the 
INRT webpage: http://www.springer.com/10791.

Submissions can be uploaded via http://www.editorialmanager.com/inrt and 
should be indicated for consideration in the Special Issue on Focused 
Retrieval and Result Aggregation"

In case you encounter any difficulties while submitting your manuscript 
online, please get in touch with the responsible Editorial Assistant by 
clicking on "CONTACT US" in the EditorialManager start page.

Authors are encouraged to contact the guest editors with any questions

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