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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>SASA- a Semi-Automatic Semantic Annotator for Personal Knowledge Management</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Kim Tighe</string-name>
          <email>ktighe@hp.com</email>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Galway</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ireland Tel.:</string-name>
        </contrib>
      </contrib-group>
      <abstract>
        <p>Best practice organisations have realised that people and their knowledge remain their greatest assets and will continue to be the largest contributory factor in obtaining future competitive advantage. Knowledge fundamentally derived from people in the absence of their understanding, personal context and application remains largely as obscure information. Current personal knowledge management (PKM) activities do not adequately support the finding, reminding, reuse and collaboration of information. In this paper we propose a novel PKM tool called SASA, a semi-automatic semantic annotator of PDF documents, which will enable collecting, connecting and collaborating of discovered information to facilitate knowledge sharing and personal content management within a business setting. SASA, a plug-in for Adobe Acrobat Professional, utilises Semantic Web technologies to enable building, augmenting and sharing of ontologies amongst knowledge workers. Within an ontology named entities are connected to additional information such as Web pages, documents, mail messages, personal notes, and wikis. SASA automatically derives the context of the document, highlights named entities and applies the relevant additional information. The business case for such a tool is outlined and user scenario development used to illustrate how SASA will assist Business Client Account Managers in the laborious process of reviewing, annotating and gathering information from customer documentation by enhancing their PKM.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Semantic Annotation</kwd>
        <kwd>Personal Knowledge Management</kwd>
        <kwd>PDF</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. INTRODUCTION</title>
      <p>
        In a rapidly changing global economy unified by improved
communication and transportation, people and their knowledge
are an organisation’s greatest assets [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. The constant emergence
of new products and competitors combined with an increasing
global marketplace are challenges facing an organisation’s ability
to survive in an increasingly unpredictable and competitive
environment. An enterprise’s continued existence will
increasingly depend upon their ability to becoming a
knowledgerich knowledge managing organisation [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]. Organisations that
focus solely on the application of their collective intellectual
capital to achieve objectives run the risk of neglecting the
fundamental truth that knowledge is derived from people [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ].
Lacking the human element of understanding, personal context
and application, knowledge within an organisation remains
largely as obscure information. Supporting individuals in their
PKM is therefore vital and will be the single largest contributory
factor in gaining future competitive advantage over the next 25
years [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
      <p>
        Enabling technologies for the WWW have provided knowledge
workers with rich information sources but have also resulted in
adding to the existing considerable volume of information that
can be searched and queried. The classical Information Retrieval
(IR) problem of identification and retrieval of current information
for activities such as informed decision making remains
problematic. The core focus of PKM is directed at improving
individual efficiency. Current activities however remain limited
lacking adequate support for the finding, reminding, reuse and
collaboration of information [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. There remains a growing need
for intuitive processes and PKM based tools to assist the worker
in evaluating not only their own knowledge but also a means to
augment it by exploration and learning from additional
information sources. Maximising human capital on a personal
level leads to enhancing individual effectiveness in a manner that
improves productivity for both the individual and enterprise [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. It
is our contention that PKM enhanced with Semantic Web
technologies can be used to assist in achieving this productivity
gain.
      </p>
      <p>
        The Semantic Web [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] envisages annotating document content by
assigning to entites in the text links to their semantic descriptions
from domain ontologies to make it easier for machines to assist
humans in finding, sharing, combining, and reusing information.
Current semantic annotation tools (e.g. KIM [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ], Trailblazer [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ]1
and tools based on Annotea2 or CREAM [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]) cater for document
annotation of Web-native formats such as HTML and XML. None
however cater for the Portable Document Format (PDF [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]3), a
format prevalent in virtually all market segments and used
extensively for document interchange and publishing.
      </p>
      <sec id="sec-1-1">
        <title>1 http://www.hp.com/ie/galway/sirg/trailblazer/</title>
      </sec>
      <sec id="sec-1-2">
        <title>2 http://www.annotae.org/</title>
      </sec>
      <sec id="sec-1-3">
        <title>3 A de facto standard on the Web alongside HTML.</title>
        <p>With the advent of the Semantic Web this paper examines how
Semantic Web enabling technologies, namely semantic annotation
can be applied to the area of PKM to enhance knowledge worker
productivity and efficiency. This paper proposes a novel tool,
SASA for semi-automatic semantic annotation of PDF
documents, which will enable collecting, connecting and
collaborating amongst knowledge workers to facilitate knowledge
sharing and personal content management within a business
setting.</p>
        <p>The remainder of this paper is structured as follows: Section 2
outlines the business case. Section 3 illustrates the scenario
development. Section 4 presents our proposed solution. Section 5
compares related work. Section 6 concludes this paper and
outlines future work.</p>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>2. BUSINESS CASE</title>
      <p>HP4 Services’ Managed Services (MS) provides customers5 with
strategic outsourcing services and solutions to manage their IT
infrastructures. The MS business unit itself is structured into a
number of areas of expertise known as towers. Each tower
specializes in a particular area such as the End User Workplace
Management (EUWM) which focuses on the end users desktop
environment. The EUWM Pre-Sales &amp; Implementation Team is
assigned Customer Relationship Management and Project
Management activities during the pre-sales and
transition/transformation stages of any customer engagement.
In each of the above activities, the EUWM consultant’s task of
understanding, interpreting and producing all relevant support
documentation is crucial for the successful proposal,
implementation and delivery of any service. Failing to adequately
capture all customer requirements, service limitations and any
assumptions made will impact customer satisfaction level, the
delivery organisations ability to succeed, HP’s profitability, and
ultimately, HP’s ability to win further contracts. Underpinning all
activities is the consultant whom has to ensure that services
scoped in the solution are delivered efficiently and implemented
in adherence to contractual obligations. For that reason, their
resulted outputs from reviewing customer documentation such as
Project Definition Document or Project Requirements Document
are essential for the project to initially commence and to continue
on-going successfully.</p>
      <p>New EUWM customer undertaking will require the consultant to
begin the laborious process of reviewing, annotating and
gathering information from on average 50 or more substantial
documents which typically are received in either Microsoft Word
or Adobe PDF format. At present, each document is manually
reviewed and annotated by the consultant. Central document
repository systems such as SharePoint6 are occasionally used for
information sharing in addition to documentation notes capture in
an associated mail or Word documents. However, it is not a
standard practice and can lead to problems of omitting key</p>
      <sec id="sec-2-1">
        <title>4 Hewlett-Packard Ltd.</title>
        <p>5</p>
        <p>Telecom/NSP, financial services,
government or public sector markets.
manufacturing
and
6 SharePoint is Microsoft collaborative management tool for
document and information sharing.
comments that are difficult to identify and retrieve particularly for
new document versions. Increasing the customer base, scope
expansion, EUWM organisational expansion and having to
comply with standards such as ISO7 frameworks has led to a
considerable increase in documentation volume and the level of
manual effort required.</p>
        <p>There is a clear opportunity for an intuitive tool that would assist
the consultants in performing documentation review and in
information gathering process in order to improve both
collaboration and traceability of document findings. Currently
under active development SASA is such a tool that offers the
semi-automatic semantic annotation of PDF documents. Its usage
will contribute towards a reduction in the level of effort required
in each new project stage, cost reduction and increased team
productivity.</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>3. SCENARIO DEVELOPMENT</title>
      <p>Take for example the situation where a EUWM client account
manager has to prepare and deliver a Project Definition Document
based on the requirements of the U.S. car manufacturing customer
“Customer X”, and the capabilities of the delivery organisation
and support structure. Material used in drawing this information
together is contained in a large number of key business
documents such as Statement of Work (SOW), HP Overall Scope
document, Technical Solution Document (TSD), RCM Model,
Overall HP-Customer Contract and Associated Schedules,
Requests For Information (RFI), Requests For Proposals (RFP),
etc.</p>
      <p>The assigned account manager firstly accesses the
transition\transformation and delivery documentation, begins the
analysis process in an attempt to identify what is of relevance to
the EUWM tower and what contractually HP are obliged to
deliver. The Overall HP-Customer Contract is opened with Adobe
Acrobat Professional and using our plug-in SASA creates the
category8 “Customer X” for the customer and begins reviewing
the documentation. With reference to Figure 1, when the account
manager identifies an item of interest such as ‘Application
Packaging’ it is added to the category as a named entity. A note of
“Due to ITAR9 U.S. government regulations all Customer X
transmissions must be manufactured within North America” is
associated with that named entity. As the account managers’
analysis progresses, another document, which is part of the
Associated Schedules documentation, is found to contain a key
stipulation regarding where UNIX application packaging must be
performed. Another note is then added to the named entity
‘Application Packaging’ along with a bookmark to document
Schedule B, which was found to have the associated information.
In this manner peripheral information obtained from sources such
as emails, phones calls and HP-Customer group discussions can
be used to filter information and associate it with suitable named
entities. Once the document review stage has concluded the
Project Definition Document write up commences. Resulting
from the review the accounts manager now has in effect a
semantically annotated information source.</p>
      <sec id="sec-3-1">
        <title>7 International Standards Organisation</title>
      </sec>
      <sec id="sec-3-2">
        <title>8 ‘Category’ is used to represent an ontology.</title>
      </sec>
      <sec id="sec-3-3">
        <title>9 International Traffic in Arms Regulations</title>
        <p>Selection of the named entity ’Application Packaging’ will
provide visibility of all additional information and annotations
from previous documentation reviews. The client account
manager also has the ability to view a summary of all the named
entites and their associated information (see Figure 2). This assists
the accounts manager in ensuring that issues regarding the like of
UNIX application packaging and ITAR regulations are factored in
and captured in the Project Definition Document. Otherwise the
potential knock on effects of overlooking this information could
adversely affect the project timeline, project scope, level of effort
required, and delivery model with ultimately negative commercial
impact.</p>
        <p>
          Referring to Figure 3, the SASA application architecture will
contain: 1) A Trainer component to train SASA using the text
and the users’ selected ontology about the context of the currently
viewed PDF document. SASA will extract the text from the
document and use a Vector Space Model (VSM) [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ]12 to
represent the collected training information by using the words
from the document and their frequency of occurrence to augment
the existing training data. 2) A Categorisation component to
derive the context of the currently viewed document using the
Cosine Similarity Measure [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ] to compare the text of the
document with the training data and calculate from the vectors the
most likely match to the current ontologies. 3) A NEIO
component to add and delete named entities and their associated
information to and from the ontology. 4) An Annotator
component to semantically annotate the text of the PDF document
by finding and highlighting named entities of interest and
applying their relevant additional information. 5) An
Import/Export component to share ontologies amongst users. 6)
A Viewer component to view an entire trail of annotations for a
selected ontology.
        </p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>4. PROPOSED SOLUTION</title>
      <p>SASA is implemented as a plug-in10 for Adobe Acrobat
Professional. SASA adds a toolbar to the standard interface (see
10 A dynamically-linked extension to Acrobat, which hooks into
the user interface and adds functionality to Acrobat
Professional, Acrobat Standard, or Adobe Reader.</p>
    </sec>
    <sec id="sec-5">
      <title>5. RELATED WORK</title>
      <p>
        SemanticWord [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ], a Microsoft Word-based environment, adds
several toolbars to the interface which support the creation of
semantic annotations in documents and templates according to
selected ontologies. Magpie [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ] is a Web browser extension
which uses Named Entity Recognition (NER) based on a supplied
11 A cross-platform API for implementing dialog interfaces for
      </p>
      <p>Adobe applications such as Acrobat, etc.
12</p>
      <p>
        An algebraic model used for information filtering and
information retrieval.
ontology of the user’s choice to highlight and add links to named
entities on a Web page. Table 1 shows an extract from a recent
survey of semantic annotation tools. It was found that they cater
primarily for Web native formats such as HTML and XML.
SASA caters for PDF and can be integrated with HPs Mozilla
Firefox extension Trailblazer [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ] to allow for HTML also.
Mark-up tied to
text regions
None, real time
      </p>
    </sec>
    <sec id="sec-6">
      <title>6. CONCLUSIONS AND FUTURE WORK</title>
      <p>In this paper we have proposed a plug-in for Adobe Acrobat
Professional called SASA, a novel PKM tool for semi-automatic
semantic annotation of PDF documents utilising Semantic Web
enabling technologies. SASA allows the user to build, augment
and share ontologies amongst knowledge workers. Within an
ontology named entities are connected to additional information
such as Web pages, documents, mail messages, personal notes,
and wikis. SASA automatically derives the context of the
document, highlights named entities and applies the relevant
additional information. The business case for such a tool is
outlined and user scenario development used to illustrate how
SASA will enhance PKM. Our future work plans, aside from
continued implementation of our SASA plug-in, include detailed
definition of the case study. We also plan to carry out a
systematic user evaluation – with the help of Client Account
Managers at HP Galway. Lastly, we are also working on
semantically annotating a number of PDF documents at the one
time and researching sub section document training.</p>
    </sec>
    <sec id="sec-7">
      <title>7. ACKNOWLEDGMENTS</title>
      <p>We would like to thank Robert Connolly and Richard Joyce from
the EUWM Pre-Sales &amp; Implementation Team, Dara Keogh, and
Colman O’Dywer from the Solutions Management Services Team
at HP Galway for their time and expertise in framing the business
case.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <surname>Nonaka</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          , (
          <year>1991</year>
          ).
          <article-title>The Knowledge Creating Company</article-title>
          . Harvard Business Review.
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <surname>Davenport</surname>
            ,
            <given-names>T. H.</given-names>
          </string-name>
          , Prusak L. “
          <string-name>
            <surname>Working</surname>
            <given-names>Knowledge</given-names>
          </string-name>
          ,
          <source>How Organisations Manage What They Know” Harvard Business School Press</source>
          <year>1997</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <surname>Nonaka</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Takeuchi</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          (
          <year>1995</year>
          ).
          <source>The Knowledge Creating Company - How Japanese Companies Create the Dynamics of Innovation</source>
          . Oxford, The Oxford University Press.
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <surname>Drucker</surname>
            ,
            <given-names>P. F.</given-names>
          </string-name>
          “
          <article-title>Managing Knowledge Means Managing Oneself” Leader to Leader</article-title>
          .
          <volume>16</volume>
          (Spring
          <year>2000</year>
          ):
          <fpage>8</fpage>
          -
          <lpage>10</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [5]
          <string-name>
            <surname>Volkel</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Oren</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          <article-title>Personal Knowledge Management with Semantic Wikis Technical Report</article-title>
          , AIFB Karlsruhe.
          <year>December 2005</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <surname>Ernst</surname>
          </string-name>
          &amp;
          <article-title>Young Center for Business Innovation</article-title>
          . (
          <year>1995</year>
          ).
          <article-title>The Financial and Non-Financial Returns to Innovative Work Practices</article-title>
          . New York: Ernst &amp; Young. March.
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <surname>Berners-Lee</surname>
            ,
            <given-names>T</given-names>
          </string-name>
          , Hendler,
          <string-name>
            <given-names>J</given-names>
            &amp;
            <surname>Lassils</surname>
          </string-name>
          ,
          <string-name>
            <surname>O.</surname>
          </string-name>
          <article-title>The Semantic Web</article-title>
          , Scientific American, May
          <year>2001</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <surname>Popov</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kirayakov</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ognyanoff</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Manov</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kirilov</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          <article-title>KIM-a semantic platform for information extraction and retrieval</article-title>
          ,
          <source>Nat. Lang. Eng</source>
          .
          <volume>10</volume>
          (
          <issue>3</issue>
          /4) (
          <year>2004</year>
          )
          <fpage>375</fpage>
          -
          <lpage>392</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <surname>Handschuh</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Staab</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Studer</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          <article-title>Leveraging metadata creation for the Semantic web with CREAM, KI '2003- advances in artificial intelligence</article-title>
          ,
          <source>in: Proceedings of the Annual German Conference on AI</source>
          ,
          <year>September 2003</year>
          ,
          <year>2003</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <given-names>Portable</given-names>
            <surname>Document Reference Manual</surname>
          </string-name>
          ,
          <string-name>
            <surname>Fifth Edition</surname>
          </string-name>
          , Adobe Systems Incorporated. http://partners.adobe.com/public/developer/pdf/index_refere nce.html
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          [11]
          <string-name>
            <surname>Brickley</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Guha. R.V.</surname>
          </string-name>
          <year>2004</year>
          .
          <source>RDF Vocabulary Description Language 1</source>
          .0:
          <string-name>
            <given-names>RDF</given-names>
            <surname>Schema</surname>
          </string-name>
          .
          <source>W3C Recommendation 10 February</source>
          <year>2004</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          [12]
          <string-name>
            <surname>Salton</surname>
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>McGill</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          <article-title>Introduction to Modern Information Retrieval</article-title>
          .
          <string-name>
            <surname>McGraw-Hill</surname>
          </string-name>
          ,
          <year>1983</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          [13]
          <string-name>
            <given-names>Van</given-names>
            <surname>Rijsbergen. C.J. Information</surname>
          </string-name>
          <string-name>
            <surname>Retrieval</surname>
          </string-name>
          ,
          <year>1979</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          [14]
          <string-name>
            <surname>Tallis</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          <article-title>SemanticWord processing for content authors</article-title>
          ,
          <source>in: Proceedings of the Knowledge Markup and Semantic Annotation Workshop (SEMANNOT</source>
          <year>2003</year>
          )
          <article-title>at 2nd International Conference on Knowledge Capture (K-CAP</article-title>
          <year>2003</year>
          ),
          <year>October 26</year>
          ,
          <year>2003</year>
          . Sanibel, Florida, USA,
          <year>2003</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          [15]
          <string-name>
            <surname>Domingue</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dzbor</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Motta</surname>
          </string-name>
          . E.
          <article-title>Collaborative Semantic Web Browsing with Magpie</article-title>
          .
          <source>In Proc. of the 1st European Semantic Web Symposium (ESWS)</source>
          ,
          <year>May 2004</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          [16]
          <string-name>
            <surname>Tighe</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Johnston</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          <article-title>Using Named Entities as a basis for sharing associative trails between Semantic Desktops</article-title>
          . 1st
          <source>International Semantic Desktop Workshop (ISWC) November</source>
          <year>2005</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          [17]
          <string-name>
            <surname>Uren</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cimiano</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Iria</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Handschuh</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Vargas-Vera</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Motta</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ciravegna</surname>
            <given-names>F</given-names>
          </string-name>
          .
          <article-title>Semantic Annotation for Knowledge Management: Requirements and a Survey of the State of the</article-title>
          <source>Art Journal of Web Semantics: Science, Services and Agents on the World Wide Web (4)</source>
          :
          <fpage>14</fpage>
          -
          <lpage>28</lpage>
          .
          <year>2006</year>
          .
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>