short-paper

Kinship contextualization: utilizing the preceding and following structural elements

Authors:

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

Pages 837 - 840

https://doi.org/10.1145/2484028.2484111

Published: 28 July 2013 Publication History

Get Access

Abstract

The textual context of an element, structurally, contains traces of evidences. Utilizing this context in scoring is called contextualization. In this study we hypothesize that the context of an XML-element originated from its \textit{preceding} and \textit{following} elements in the sequential ordering of a document improves the quality of retrieval. In the tree form of the document's structure, \textit{kinship} contextualization means, contextualization based on the horizontal and vertical elements in the \textit{kinship tree,} or elements in closer to a wider structural kinship. We have tested several variants of kinship contextualization and verified notable improvements in comparison with the baseline system and gold standards in the retrieval of focused elements.

References

[1]

P. Arvola, M. Junkkari, and J. Kekäläinen. Generalized Contextualization Method for XML Information Retrieval. In Proc. of the 14th ACM CIKM, pages 20--27. ACM, 2005.

Digital Library

Google Scholar

[2]

P. Arvola, J. Kekäläinen, and M. Junkkari. The Effect of Contextualization at Different Granularity Levels in Content-oriented XML Retrieval. In Proc. of the 17th ACM CIKM, pages 1491--1492. ACM, 2008.

Digital Library

Google Scholar

[3]

P. Arvola, J. Kek\"al\"ainen, and M. Junkkari. Contextualization Models for XML Retrieval. Info. Processing & Management, pages 1--15, 2011.

Digital Library

Google Scholar

[4]

S. Geva, J. Kamps, M. Lethonen, R. Schenkel, J. Thom, and A. Trotman. Overview of the inex 2009 ad hoc track. Focused Retrieval and Evaluation, pages 4--25, 2010.

Crossref

Google Scholar

[5]

Y. Mass and M. Mandelbrod. Component Ranking and Automatic Query Refinement for XML Retrieval. Advances in XML IR, pages 1--18, 2005.

Digital Library

Google Scholar

[6]

M. A. Norozi, P. Arvola, and A. P. de Vries. Contextualization using hyperlinks and internal hierarchical structure of wikipedia documents. In Proc. of the 21st ACM CIKM, pages 734--743. ACM, 2012.

Digital Library

Google Scholar

[7]

P. Ogilvie and J. Callan. Hierarchical Language Models for XML Component Retrieval. Advances in XML IR, pages 269--285, 2005.

Digital Library

Google Scholar

[8]

G. Ramirez Camps. Structural Features in XML Retrieval. D thesis, SIKS, the Dutch Research School for Information and Knowledge Systems., 2007.

Google Scholar

[9]

Schenkel, R. and Suchanek, F.M. and Kasneci, G. YAWN: A Semantically Annotated Wikipedia XML Corpus. Proc. of GIFachtagung für Datenbanksysteme in Business Technologie und Web BTW2007, 103 (Btw): 277--291, 2007.

Google Scholar

[10]

J. A. Shaw and E. A. Fox. Combination of multiple searches. In The 2nd TREC. Citeseer, 1994.

Google Scholar

[11]

B. Sigurbjörnsson, J. Kamps, and M. De Rijke. An Element-based Approach to XML Retrieval. In INEX 2003 Workshop Proc., pages 19--26, 2004.

Google Scholar

Cited By

View all

Albarede LMulhem PGoeuriot LMarié SLe Pape-Gardeux CChardin-Segui T(2023)Heterogeneous graph attention networks for passage retrievalInformation Retrieval10.1007/s10791-023-09424-326:1-2Online publication date: 16-Nov-2023
https://dl.acm.org/doi/10.1007/s10791-023-09424-3
Albarede LMulhem PGoeuriot LLe Pape-Gardeux CMarie SChardin-Segui T(2022)Passage Retrieval on Structured Documents Using Graph Attention NetworksAdvances in Information Retrieval10.1007/978-3-030-99739-7_2(13-21)Online publication date: 10-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-030-99739-7_2
Kekäläinen JArvola PJunkkari M(2018)Contextualization in Structured Text RetrievalEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_81(611-613)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_81
Show More Cited By

Index Terms

Kinship contextualization: utilizing the preceding and following structural elements
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

Recommendations

Contextualization using hyperlinks and internal hierarchical structure of Wikipedia documents
CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

Context surrounding hyperlinked semi-structured documents, externally in the form of citations and internally in the form of hierarchical structure, contains a wealth of useful but implicit evidence about a document's relevance. These rich sources of ...
Contextualization models for XML retrieval

In a hierarchical XML structure, surrounding elements form the context of an XML element. In document-oriented XML, the context is a part of the semantics of the element and augments its textual information. The process of taking the context of the ...
Generalized contextualization method for XML information retrieval
CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management

A general re-weighting method, called contextualization, for more efficient element ranking in XML retrieval is introduced. Re-weighting is based on the idea of using the ancestors of an element as a context: if the element appears in a good context -- ...

Comments

Information & Contributors

Information

Published In

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

July 2013

1188 pages

ISBN:9781450320344

DOI:10.1145/2484028

General Chairs:
Gareth J.F. Jones
Dublin City University, Ireland
,
Páraic Sheridan
Dublin City University, Ireland
,
Program Chairs:
Diane Kelly
University of North Carolina, Chapel Hill, USA
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Tetsuya Sakai
Microsoft Research Asia, China

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

SIGIR '13

Sponsor:

SIGIR

SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval

July 28 - August 1, 2013

Dublin, Ireland

Acceptance Rates

SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
140
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 15 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Albarede LMulhem PGoeuriot LMarié SLe Pape-Gardeux CChardin-Segui T(2023)Heterogeneous graph attention networks for passage retrievalInformation Retrieval10.1007/s10791-023-09424-326:1-2Online publication date: 16-Nov-2023
https://dl.acm.org/doi/10.1007/s10791-023-09424-3
Albarede LMulhem PGoeuriot LLe Pape-Gardeux CMarie SChardin-Segui T(2022)Passage Retrieval on Structured Documents Using Graph Attention NetworksAdvances in Information Retrieval10.1007/978-3-030-99739-7_2(13-21)Online publication date: 10-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-030-99739-7_2
Kekäläinen JArvola PJunkkari M(2018)Contextualization in Structured Text RetrievalEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_81(611-613)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_81
Kekäläinen JArvola PJunkkari M(2017)Contextualization in Structured Text RetrievalEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_81-2(1-3)Online publication date: 31-Jul-2017
https://doi.org/10.1007/978-1-4899-7993-3_81-2
Norozi MArvola PHe QIyengar ANejdl WPei JRastogi R(2013)Selection fusion in semi-structured retrievalProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505686(1291-1300)Online publication date: 27-Oct-2013
https://dl.acm.org/doi/10.1145/2505515.2505686

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Contextualization using hyperlinks and internal hierarchical structure of Wikipedia documents

Contextualization models for XML retrieval

Generalized contextualization method for XML information retrieval