Towards Contextual and Structural Relevance Feedback in

XML Retrieval

Lobna HlaouaIRIT (Institut de Recherche en Informatique de Toulouse)

Equipe SIG-RI (Systèmes d’Informations Généralisées)

118, route de Narbonne - 31062 Toulouse cedex 04

Outline

• Context

• Relevance Feedback in XML Retrieval

• Contextual Relevance Feedback

• Structural Relevance Feedback

• Conclusion & prospects

Context: XML Retrieval

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Traditional IR

- Document is atomic unit

- user can be submerged by noisy subjects

Context: XML Retrieval

<book date-publi=‘2000’><title> Ontologies </title><author> J.Dupond</author><chapter>

<title> history of ontology </title><section num= "1" >

<title> Introduction</title><para> ...ontology should be seen only as

an interdiscipline... </para></section><section num= " 2 " > <title> What is Ontology</title>

<para> ...An ontology is an explicit specification of a conceptualization... </para>

<para> In the philosophical sense, we may refer to an ontology as a particular system of categories accounting for a certain vision of the world….. </para>

</section></chapter><chapter> …. </chapter></book>

XML Retrieval

- different granularities

Context: XML Retrieval

<article date-publi=‘2000’><title> Ontologies </title><author> J.Dupond</author><chapter>

<title> history of ontology </title><section num= "1" >

<title> Introduction</title><para> ...ontology should be seen only as

an interdiscipline... </para></section><section num= " 2 " > <title> What is Ontology</title>

<para> ...An ontology is an explicit specification of a conceptualization... </para>

<para> In the philosophical sense, we may refer to an ontology as a particular system of categories accounting for a certain vision of the world….. </para>

</section></chapter><chapter> …. </chapter></article>

« ontologies case study »

- CAS (Content And Structure) Ex:

- CO (Content Only) Ex:

« //article[about(.,ontologies)]//sec[about(., ontologies case study)] »

«//article[about(.,ontologies)]»

«//article[about(.,ontologies)]//para[about(., ontologies case study)] »

<para> In the philosophical sense, we may refer to an ontology as a particular system of categories accounting for a certain vision of the world….. </para>

<section num= " 2 " > <title> What is Ontology</title>

<para> ...An ontology is an explicit specification of a conceptualization... </para>

<para> In the philosophical sense, we may refer to an ontology as a particular system of categories accounting for a certain vision of the world….. </para>

</section>

<article date-publi=‘2000’><title> Ontologies </title><author> J.Dupond</author><chapter>

<title> history of ontology </title><section num= "1" >

<title> Introduction</title><para> ...ontology should be seen only as an

interdiscipline... </para></section><section num= " 2 " > <title> What is Ontology</title>

<para> ...An ontology is an explicit specification of a conceptualization... </para>

<para> In the philosophical sense, we may refer to an ontology as a particular system of categories accounting for a certain vision of the world….. </para>

</section></chapter><chapter> …. </chapter></article>

Relevance Feedback (RF)

• RF in traditional IR consists in enriching the initial query using terms extracted from relevant documents.

• How RF can be used in XML retrieval ?

Relevance Feedback (RF) in XML

Retrieval • Problems

– How extracting terms from retrieved elements having different semantic

• element could (title, section, paragraph, etc.)

• … whereas in IR only document units are considered

– How structural constraints can be extracted from relevant elements

– How enriching XML queries : • adding structural constraints And/OR keywords in both

CO and CAS queries?

Our approach

• Contextual RF– expand the query with expressive words according to

the context of the judged component from different granularities.

• Structural RF– select the more appropriate generative structure from

judged components and adding to CO query.

Process of RF in XML Retrieval

Relevant components

Extraction of expressive terms

Extraction of relevant structure

Initial query

Relevance Feedback

Reformulated query

Results RC+ NRC

• Objective: select the more expressive words

• Let’s consider Er={er1, er

2, ..., erk,... er

m} , erk

={l1,..., lj,.ln} – assign a score to terms (ti) occurring in each leaf node (lj) of the relevant elements.

– Compute the score of terms of in each element (erk).

– Select the best terms according to number of occurrence in relevant elements.

Contextual Relevance Feedback

)(

),(),(

j

jiji lcard

ltnfltscore

),(),( jel

irki ltscoreetscore

kr

j

),()( kEe

ii ttscoretscorerr

k

Structural Relevance Feedback

• Objective is to select the more appropriate generative structure – retrieve the smallest common ancestor– attribute scores for each structure

dn

i iSSscore Si is the structure of relevant element having a joint base with the candidate structuren is a number of the relevant elementsd is the distance which separates nodes is a constant vaying in [0,1]

Example of RF in CO query

• Initial query Q: “information retrieval”

• Structural RF – we suppose that relevant structures have the following

scores:• /book/chapter/section/subsection (0.4)

• /book/chapter/section/subsection/para (0.4)

• /book/chapter/section/title (0.2)

Q2: “article//sec[about(., information retrieval)] ”

Conclusion & prospects

• Outlined the problem of Relevance Feedback in XML Retrieval.

• New challenge in IR : up until now only very few related works

• Our investigations can be considered as a first step of a long hard work.

• The main idea behind theses investigations:– how keywords and structural constraints can be selected and added

to CO queries.

• Experiments will be carried out “soon” in INEX framework

THANK YOU

Contextual Relevance Feedback

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