<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Media Watch on Climate Change: Building and Visualizing Contextualized Information Spaces</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Arno Scharl</string-name>
          <email>scharl@ecoresearch.net</email>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Albert Weichselbraun</string-name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Alexander Hubmann-Haidvogel</string-name>
          <email>alexander.hubmann@wu-wien.ac.at</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Hermann Stern</string-name>
          <email>hermann.stern@tugraz.at</email>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Gerhard Wohlgenannt</string-name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Dmytro Zibold</string-name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of New Media Technology MODUL University Vienna</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Institute for Tourism and Leisure Studies Vienna University of Economics and Business Administration</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Knowledge Management Institute Graz University of Technology</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Research Institute for Computational Methods Vienna University of Economics and Business Administration</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>This paper presents the 'Media Watch on Climate Change', an interactive Web portal that combines a portfolio of semantic services with a visual interface based on tightly coupled views. The interface enables users to access a repository of environmental knowledge, built by crawling about 300,000 news media articles in weekly intervals. Tagging services annotate each article to create a contextualized information space. A system component for automatically extending ontologies helps structure the knowledge repository, and feeds an ontology-based visualization module. The Web portal is intended to facilitate the access of complex datasets, help users navigate large collections of Web documents based on similarity, geospatial context and underlying concept, and provide annotations via standardized interfaces for third-party applications.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>The widespread acceptance of three-dimensional virtual globes such as Google Earth
and NASA World Wind advances the vision of a Geospatial Web. The following
hypothetical scenario outlines how an integration of geospatial and semantic data may
radically change working environments, impact workflows within and across
organizations, and enrich individual interactions.</p>
      <p>“Kathryn O’Reilly is a freelance editor who sells her ability to gather, filter and
prioritize electronic content. In a virtual world built on contextualized information spaces,
Kathryn seamlessly switches between geographic and semantic topologies. She begins
her typical working day floating in the virtual space above Earth, ready to navigate
the globe and semantic structures via subtle movements of her eyes. From her elevated
position, Kathryn not only observes the rise and decay of topics, but also the unfolding
of social structures based on the unique social networks of her friends and contacts.
Across these networks she builds and shares her knowledge repository, and composes
media products that are continuously being validated and enriched by the latest news
feeds and third-party sources” [1, p.3f].</p>
      <p>This scenario exemplifies the profound impact of the Geospatial Web on managing
individual and organizational knowledge. The Geospatial Web will not only reveal the
context and geographic distribution of location-based resources and services, but also
catalyze virtual communities by matching people of similar interests, browsing
behavior, or geographic location.
2</p>
      <p>
        System Description
The vision of a Geospatial Web promotes the convergence of geographic information,
Internet technology and social change. Taking a step towards this vision, the Media
Watch on Climate Change uses automated content analysis to extract geospatial context
and build a geotagged knowledge base. The interface provides various means to
interactively access this knowledge base. It shows that geobrowsers are not only suited to
explore geographic features, but can also render other types of imagery such as
twodimensional semantic maps or three-dimensional knowledge planets. Such maps are
representations of semantic information spaces based on a landscape metaphor [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ].
      </p>
      <p>To increase awareness and the availability of environmental information, the IDIOM
Media Watch on Climate Change provides a comprehensive and continuously updated
account of media coverage on climate change and related issues. The portal aggregates,
filters and visualizes environmental Web content from 150 Anglo-American news
media sites. It is available at the following address:</p>
      <p>http://www.ecoresearch.net/iswc2007
2.1</p>
    </sec>
    <sec id="sec-2">
      <title>Annotation and Data Management</title>
      <p>The knowledge base underlying the Media Watch on Climate Change is a
contextualized information space. If authors and information providers do not provide contextual
attributes, annotation services attempt to tag and classify new objects. If contextual
attributes are provided, the annotation services validate the manual entries, add missing
information, and suggest changes if conflicting information is found. The annotation
services of the current prototype provide metadata along three dimensions: (i) spatial
distinguishing between source and target geography; (ii) semantic - assigning the most
relevant concepts from a controlled vocabulary; and (iii) temporal - adding timestamps
for the reported event, the initial publication and subsequent revisions. Each element of
the contextualized information space can be organized, indexed, searched and navigated
along these dimensions.</p>
    </sec>
    <sec id="sec-3">
      <title>2.2 Interface Design and Map Synchronization</title>
      <p>Figure 1 shows a screenshot of the current prototype. The content view in the upper left
window contains the active document, including its mirror date and source/target
geography. Below, just-in-time information retrieval agents list documents referring to
similar topics and nearby locations. Clicking on the related references extends the quoted
text, clicking on the circular marker on the left activates that particular document. The
semantic and geographic maps facilitate access to the underlying knowledge base. The
information landscape in the upper right window shows the semantic associations
between documents. Peaks indicate clusters of documents about a popular topic, whereas
valleys represent sparsely populated parts of the information space. The two links in the
upper left corner of this window allow users to switch between the semantic map and a
visual representation of an automatically generated domain ontology (see Section 2.5).
Below, a geographic map shows the locations referred to in the listed documents.
Clicking on the ’max’ links increases the size of the maps.</p>
      <p>Each of the ’3D’ links opens a new window. The semantic map links to a description
of knowledge planets as a new interface metaphor. The link of the geographic map
points towards a KML (Keyhole Markup Language) file that requires a geobrowser to
display the 100 most relevant news items on a three-dimensional virtual globe.</p>
      <p>Once users enter a search query, an additional window displays quotes including
the target term as ’concordances’ (centering the target term and showing its immediate
context in the various documents). Besides entering query terms, users can click on any
position in the maps (not only on the document markers) to retrieve articles related to
that particular location, topic, or domain concept. The different views are therefore said
to be ’tightly coupled’: User actions in one window trigger an immediate update of all
other displays.</p>
    </sec>
    <sec id="sec-4">
      <title>2.3 Integration of Semantic Markup and Interoperability</title>
      <p>Microformats like hCard, hCalendar, XFN and others provide straightforward
techniques to embed semantically rich information into existing Web pages. Their markup
is not as advanced and powerful as RDF, but aggregator services like Technorati have
demonstrated how useful these tagging formats content have become. Within fifteen
months, from November 2005 to April 2006, the number of tagged postings grew from
zero to 100 million5.</p>
      <p>Web2.0 sites like Dopplr.com6 or CouchSurfing.com7 started adapting
microformats for building social networks using XFN and the hCard standard. “IBM is
another early adaptor, enriching employee listings with hCards information. Unfolding the
power of a decentralized and easy tagging architecture, Web developers and domain
experts specify new domain-specific microformats in order to provide users with a steadily
growing vocabulary for annotating Web content. Efforts like the W3C’s development of
RDFa try to combine the advantages of micro-formats with the expressiveness of RDF.</p>
      <p>’Geo’ microformats describe the target geography of the IDIOM Media Watch’s
documents by encoding geographical information. ’Rel-tag’ markup extends existing
hyperlinks, marking the destination as a system-designated tag. Data from the
just-intime information retrieval agents is annotated using the ’hReview’ microformat,
marking it as a review and thus giving it additional information such as a relevance rating
and a review date. Browser add-ons such as the “Operator” and “Tails Export”
Firefox extensions provide a user-friendly interface for importing such entries into existing
applications. Geo-metadata from the IDIOM Media Watch prototype can be presented
as a link to mapping applications such as Yahoo! or Google Maps, ’rel-tag’ markup
refers the user to community sites such as del.icio.us8 and flickr9. RSS feeds provide
annotated document feeds to topics and keywords promoting interoperability with third
party applications. The feeds are available at the following address:
2.4</p>
    </sec>
    <sec id="sec-5">
      <title>Knowledge Planets</title>
      <p>Generated by orthographically projecting and tiling semantic maps (= visual
representations of semantic information spaces based on a landscape metaphor), knowledge
planets allow visualizing massive amounts of textual data. At the time of map
generation, the planet’s topology is determined by the content of the knowledge base. The
peaks of the virtual landscape indicate abundant coverage on a particular topic, whereas
valleys represent sparsely populated parts of the information space.</p>
      <p>
        VisIslands, a thematic mapping algorithm similar to SPIRE’s Themescape [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] and
its commercial successor Cartia/Aureka, supports dynamic document clustering [
        <xref ref-type="bibr" rid="ref4 ref5">4, 5</xref>
        ].
Initially, the document set is pre-clustered using hierarchical agglomerative clustering
5 http://www.digital-web.com/articles/the big picture on microformats/
6 http://dopplr.com/
7 http://www.couchsurfing.com/
8 http://del.icio.us/
9 http://www.flickr.com/
[
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], randomly distributing the cluster centroids in the viewing rectangle. The
documents belonging to each cluster, as determined by the pre-clustering, are then placed
in circles around each centroid. The arrangement is fine-tuned using a linear iteration
force-directed placement algorithm adapted from Chalmers [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]. The result resembles
a contour map of islands. Fortunately, algorithms based on force models easily
generalize to the knowledge planets’ spherical geometries. The IDIOM research project
(www.idiom.at) extends and refines the VisIslands thematic mapping component to
improve throughput and scalability, generate layered thematic maps, and provide a Web
Map Service (WMS) that serves these maps as image tiles for various geobrowsing
platforms.
2.5
      </p>
    </sec>
    <sec id="sec-6">
      <title>Ontology Extension</title>
      <p>
        The need for controlled vocabularies and shared meaning suggests that ontologies
shared conceptualizations within a specific domain [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] - are going to play a key role
in managing context information. Geo-ontologies encode geographical terms and
semantic relationships such as containment, overlap and adjacency. Domain ontologies
are used to organize topics and to navigate through knowledge repositories. Spatially
aware search engines use ontological knowledge for query term expansion and
disambiguation, relevance ranking and Web resource annotation [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]. This project does not
intend to generate a universally accepted domain ontology, but to accurately represent
knowledge contained within a specific corpus. Changes in sample composition or trends
in media coverage inevitably affect the generated ontology. This represents a promising
avenue for comparative studies and future research on ontology evolution.
target corpus ref corpus
external source
      </p>
      <p>Domain Expert(s)</p>
      <sec id="sec-6-1">
        <title>Trigger</title>
      </sec>
      <sec id="sec-6-2">
        <title>Phrases</title>
        <p>Hearst Patterns</p>
      </sec>
      <sec id="sec-6-3">
        <title>Co-Occurrence</title>
      </sec>
      <sec id="sec-6-4">
        <title>Analysis</title>
        <p>Sentence-Level
Page-Level</p>
      </sec>
      <sec id="sec-6-5">
        <title>Lexical</title>
      </sec>
      <sec id="sec-6-6">
        <title>Analyzer</title>
      </sec>
      <sec id="sec-6-7">
        <title>Disambiguation</title>
        <p>WordNet
Seed Ontology
Extended Ontology</p>
      </sec>
      <sec id="sec-6-8">
        <title>Semantic</title>
      </sec>
      <sec id="sec-6-9">
        <title>Network</title>
      </sec>
      <sec id="sec-6-10">
        <title>Concept</title>
      </sec>
      <sec id="sec-6-11">
        <title>Positioning</title>
      </sec>
      <sec id="sec-6-12">
        <title>Most Active</title>
      </sec>
      <sec id="sec-6-13">
        <title>Concepts</title>
        <p>Spr/Activation</p>
      </sec>
      <sec id="sec-6-14">
        <title>Relationship</title>
      </sec>
      <sec id="sec-6-15">
        <title>Discovery</title>
        <p>Spr/Activation
Head Nouns</p>
        <p>WordNet</p>
        <p>Due to the sheer volume of data, the use of ontologies in large information spaces is
difficult without an ontology extension system that suggests concepts and relations
automatically. Figure 2 presents a conceptual view of the ontology extension architecture
underlying the Media Watch on Climate Change.</p>
        <p>
          A small set of terms obtained from domain experts or known ontology repositories
is first selected as a seed ontology. The seed ontology terms are then fed into the
analyzer, which is distributing the input to different plugins that provide evidence sources,
suggesting promising new concepts. Currently three evidence sources are considered:
1. Co-occurrence analysis [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ] at both the sentence and the document level uses a
threshold based on the co-occurrence significance to select 20 terms on the sentence
and 20 terms on the document level.
2. Trigger Phrases [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ] matching a fragment of text that indicates a particular relation
between terms (e.g. parent-child relation).
3. The WordNet lexical dictionary [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ], which is used as additional evidence source
after disambiguating the seed ontology’s concepts using a vector space model.
The generated terms are then connected with a seed ontology via directed weighted
links. Once the network is established, a spreading activation algorithm identifies the
most relevant terms and suggests their incorporation into the seed ontology as described
in Wei et al. [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ]. Then the following heuristic is used to determine their relation to the
concepts in the seed ontology: (i) WordNet, head noun analysis and additional rounds
of spreading activation determine the new concepts’ position within the ontology, (ii)
Subsumption analysis together with WordNet and head noun analysis identify the
semantic relation’s type. For terms not confirmed automatically, domain experts are
consulted. Optionally another iteration of spreading activation over newly acquired terms
is triggered to integrate additional concepts into the ontology. In Figure 3, the concepts’
shading differentiates the seed ontology terms (= lighter shading) from those added in
several iterations of automated ontology learning.
2.6
        </p>
      </sec>
    </sec>
    <sec id="sec-7">
      <title>Ontology Visualization</title>
      <p>Ontologies retrieved from the ontology extension process are serialized in OWL and
then fed into the visualization framework. Transforming relations annotated using
reification and all other information encoded in the serialized version of the ontology into
the graphviz10 description language yields an SVG-file with a graphical representation
of the ontology. The framework extracts the concepts’ positions from the SVG files,
which provides the mapping required for interactions with the ontology view.</p>
      <p>Applying the iterative ontology extension process to 50 Web sites mirrored in July
2007 and comprising approximately 80,000 documents yielded the Web portal’s domain
ontology (see Figure 3). Arrows indicate confirmed hierarchical relations. The dotted
lines connect semantically related terms whose exact type of relation could not be
determined automatically. For these non-hierarchical relations, the (r) values indicate their
strength based on the link assignment’s spreading activation level. High values suggest
a strong relation between the concepts, a value of 8 being the maximum due to the
specific setup of the spreading activation network.</p>
      <p>The current navigational aid contains unlabeled associations, only indicating the
strength of the relation but not its specific type. The IDIOM research project is currently
extending the underlying algorithm to detect a much broader set of relation types
10 http://www.graphviz.org/
Current applications only hint at the true potential of geospatial technology to build
and maintain virtual communities and to revolutionize the production, distribution and
consumption of media products. Automatically annotating content from heterogeneous
sources creates knowledge repositories spanning multiple dimensions such as space,
time, and semantics.</p>
      <p>
        Virtual globes improve the accessibility and transparency of such complex
repositories. Their introduction has popularized the process of “annotating the Planet” [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ].
This process yields geospatially referenced information, enabling virtual globes to map
annotated content units from various sources. But geospatial interfaces can also serve
as a generic image rendering engine to project other types of imagery.
      </p>
      <p>The Media Watch on Climate Change demonstrates how geospatial interfaces can
be used to visualize layered representations of thematic maps and domain ontologies as
a frontend for semantic services.</p>
    </sec>
    <sec id="sec-8">
      <title>Acknowledgment</title>
      <p>The Media Watch on Climate Change has been developed as part of IDIOM
(Information Diffusion across Interactive Online Media; www.idiom.at), a research project
funded by the Austrian Ministry of Transport, Innovation &amp; Technology (BMVIT) and
the Austrian Research Promotion Agency (FFG) within the strategic objective FIT-IT
(www.fit-it.at).</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Scharl</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>Towards the geospatial web: Media platforms for managing geotagged knowledge repositories</article-title>
          . In Scharl,
          <string-name>
            <given-names>A.</given-names>
            ,
            <surname>Tochtermann</surname>
          </string-name>
          , K., eds.: The Geospatial Web - How
          <string-name>
            <surname>Geobrowsers</surname>
          </string-name>
          ,
          <source>Social Software and the Web 2.0 are Shaping the Network Society</source>
          . Springer, London (
          <year>2007</year>
          )
          <fpage>3</fpage>
          -
          <lpage>14</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Chalmers</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          :
          <article-title>Using a landscape metaphor to represent a corpus of documents</article-title>
          . In Frank, A.U.,
          <string-name>
            <surname>Campari</surname>
          </string-name>
          , I., eds.
          <source>: Spatial Information Theory: A Theoretical Basis for GIS (Lecture Notes in Computer Science</source>
          , Vol
          <volume>716</volume>
          ). Springer, Berlin (
          <year>1993</year>
          )
          <fpage>377</fpage>
          -
          <lpage>390</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Wise</surname>
            ,
            <given-names>J.A.</given-names>
          </string-name>
          :
          <article-title>The ecological approach to text visualization</article-title>
          .
          <source>Journal of the American Society for Science</source>
          <volume>50</volume>
          (
          <issue>9</issue>
          ) (
          <year>1999</year>
          )
          <fpage>814</fpage>
          -
          <lpage>835</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <surname>Andrews</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Guetl</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Moser</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Sabol</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Lackner</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          :
          <article-title>Search result visualisation with xfind</article-title>
          . In Kapetanios, E.,
          <string-name>
            <surname>Hinterberger</surname>
          </string-name>
          , H., eds.: Second International Workshop on User Interfaces to Data
          <source>Intensive Systems (UIDIS</source>
          <year>2001</year>
          ), Zurich, Switzerland, IEEE Press (
          <year>2001</year>
          )
          <fpage>50</fpage>
          -
          <lpage>58</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Sabol</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kienreich</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Granitzer</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Becker</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Tochtermann</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Andrews</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          :
          <article-title>Applications of a lightweight, web-based retrieval, clustering, and visualisation framework</article-title>
          . In Karagiannis, D.,
          <string-name>
            <surname>Reimer</surname>
          </string-name>
          , U., eds.
          <source>: 4th International Conference on Practical Aspects of Knowledge Management (Lecture Notes in Computer Science</source>
          , Vol
          <volume>2569</volume>
          ). Springer, Berlin (
          <year>2002</year>
          )
          <fpage>359</fpage>
          -
          <lpage>368</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <surname>Jain</surname>
            , Anil,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Murty</surname>
            ,
            <given-names>M.N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Flynn</surname>
            ,
            <given-names>P.J.</given-names>
          </string-name>
          :
          <article-title>Data clustering: A review</article-title>
          .
          <source>ACM Computing Surveys</source>
          <volume>31</volume>
          (
          <issue>3</issue>
          ) (
          <year>1999</year>
          )
          <fpage>264</fpage>
          -
          <lpage>323</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7.
          <string-name>
            <surname>Chalmers</surname>
            ,
            <given-names>M.:</given-names>
          </string-name>
          <article-title>A linear iteration time layout algorithm for visualising high-dimensional data</article-title>
          .
          <source>In: 7th Conference on Visualization</source>
          , San Francisco, USA, IEEE Computer Society (
          <year>1996</year>
          )
          <fpage>127</fpage>
          -
          <lpage>132</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <surname>Gahleitner</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Behrendt</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Palkoska</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Weippl</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          :
          <article-title>Knowledge sharing and reuse: On cooperatively creating dynamic ontologies</article-title>
          .
          <source>In: 16th ACM Conference on Hypertext and Hypermedia (Hypertext-2005)</source>
          , Salzburg, Austria, ACM Press (
          <year>2005</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <surname>Abdelmoty</surname>
            ,
            <given-names>A.I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Smart</surname>
            ,
            <given-names>P.D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jones</surname>
            ,
            <given-names>C.B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Fu</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Finch</surname>
            ,
            <given-names>D.:</given-names>
          </string-name>
          <article-title>A critical evaluation of ontology languages for geographic information retrieval on the internet</article-title>
          .
          <source>Journal of Visual Languages and Computing</source>
          <volume>16</volume>
          (
          <issue>4</issue>
          ) (
          <year>2005</year>
          )
          <fpage>331</fpage>
          -
          <lpage>358</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10.
          <string-name>
            <surname>Roussinov</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Zhao</surname>
            ,
            <given-names>J.L.</given-names>
          </string-name>
          :
          <article-title>Automatic discovery of similarity relationships through web mining</article-title>
          .
          <source>Decision Support Systems</source>
          <volume>35</volume>
          (
          <year>2003</year>
          )
          <fpage>149</fpage>
          -
          <lpage>166</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11.
          <string-name>
            <surname>Joho</surname>
            ,
            <given-names>H.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Sanderson</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Beaulieu</surname>
            ,
            <given-names>M.:</given-names>
          </string-name>
          <article-title>A study of user interaction with a concept-based interactive query expansion support tool</article-title>
          .
          <source>In: Advances in Information Retrieval, 26th European Conference on Information Retrieval</source>
          . (
          <year>2004</year>
          )
          <fpage>42</fpage>
          -
          <lpage>56</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <surname>Fellbaum</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          :
          <article-title>Wordnet an electronic lexical database</article-title>
          .
          <source>Computational Linguistics</source>
          <volume>25</volume>
          (
          <issue>2</issue>
          ) (
          <year>1998</year>
          )
          <fpage>292</fpage>
          -
          <lpage>296</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          13.
          <string-name>
            <surname>Liu</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Weichselbraun</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Scharl</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chang</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          :
          <article-title>Semi-automatic ontology extension using spreading activation</article-title>
          .
          <source>Journal of Universal Knowledge Management</source>
          <volume>0</volume>
          (
          <issue>1</issue>
          ) (
          <year>2005</year>
          )
          <fpage>50</fpage>
          -
          <lpage>58</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          14.
          <string-name>
            <surname>Udell</surname>
          </string-name>
          , J.:
          <article-title>Annotating the planet with google maps</article-title>
          .
          <source>InfoWorld March</source>
          <volume>04</volume>
          (
          <year>2005</year>
          )
          <article-title>www</article-title>
          .infoworld.com/article/05/03/04/10OPstrategic 1.html.
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>