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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Ontology-supported Exploratory Search for Physical Training Exercises</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Michael Kotzyba</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Denis Ponomaryov</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Thomas Low</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Marcus Thiel</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Birte Glimm</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Andreas Nu¨rnberger</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Data and Knowledge Engineering Group, Otto von Guericke University Magdeburg</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Institute of Artificial Intelligence, University of Ulm</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>In order to provide a qualitative support to the users during a web search, it is important to have access to a multitude of information sources simultaneously. Depending on the available domain expertise, the user can get an overview and insight to different information perspectives and compare the quality of resources. In this work, we present an exploratory search engine that simultaneously accesses internet resources and a local knowledge base given in the form of ontologies. The ontologies are used to define the search context and can be extended during exploration with new information, thus making the search process adaptive and iterative. We demonstrate our system on an example from the fitness domain, where the user searches for physical training exercises on the Web to complete a personal training plan.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Introduction</title>
      <p>To address the increasing variety of information published on the Web, different
techniques have been developed to support users in information retrieval (IR).
Index structures allow for searching for arbitrary keywords, query suggestions
help the user in formulating the information need, summarizing surrogates and
thumbnails facilitate preselection, while personalization helps to increase search
performance. With the development of the Semantic Web and the increasing
amount of domain-specific ontologies, more advanced techniques for IR have
appeared that make use of semantics to support the user during search.</p>
      <p>We present an implementation of a search engine, that accesses internet
resources and local ontologies simultaneously to support the user during exploratory
search, and allows for extending a personal ontology on demand. We illustrate how
the system works with a use case from the fitness domain, where a user is creating
a training plan using a fitness planner. A user searches for a specific fitness
training exercise, because the exercise is not yet listed in the knowledge base of the
fitness planner. The general approach, namely to search for missing information
to complete a knowledge base and simultaneously use the same knowledge base to
support the user, is of course not limited to this scenario. A demonstration video
of the application is available at http://www.dke.ovgu.de/ISWC2015.html.</p>
    </sec>
    <sec id="sec-2">
      <title>Related Work</title>
      <p>
        Ontologies are traditionally used to support information retrieval tasks. Crampes
and Ranwez [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ] discuss strategies and formulate principles of conceptional
navigation based on ontologies with the goal of improving navigation in the Web. Yang
et al. [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] propose an ontology-based FAQ system, which processes user queries
to enhance ranking techniques. Yang and Ho [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] show that user models can be
improved by using domain-specific ontologies. The system by Fensel at al. [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]
operates with Web resources and employs background ontologies to provide a
homogeneous access to information. Keeping in mind the complexity and variety
of Web resources, it still cannot be guaranteed that no important information is
omitted when using the homogeneous access. In contrast, our approach allows for
exploring not only Web resources, but also the content of background ontologies
contained in the system, which can be dynamically extended with user-specific
knowledge. Thus, we argue that instead of an accumulated, homogenous view,
a separated view for the ontological knowledge is required in order to improve
search effectiveness and user experience.
3
      </p>
    </sec>
    <sec id="sec-3">
      <title>Ontology-supported Exercise Search</title>
      <p>
        We consider a scenario in which a user interacts with a system designed to provide
personal training assistance. The system contains knowledge about the fitness
domain which forms the basis for suggestions of training programs to the user.
The system stores a list of fitness exercises that can be combined into training
programs and is open for updates from external information sources available
on the Web. In the demo, we address the situation when a user wants to add a
new exercise to the system’s knowledge base in order to use it in an individual
training program. The user initiates an online search for spine therapy exercises,
which is guided by the system knowledge base given as a collection of ontologies.
This search can be categorized as exploratory search [
        <xref ref-type="bibr" rid="ref5 ref6">5,6</xref>
        ], since the user is not
sure about a specific exercise to search for, and thus needs support in exploring
possible alternatives.
3.1
      </p>
      <sec id="sec-3-1">
        <title>Ontologies</title>
        <p>The core component of the system’s knowledge base is the domain ontology. It
contains categorized exercises, each of which is provided with textual descriptions
such as preparation, execution, and comment. For every exercise, the required
fitness equipment, as well as corresponding target and synergist muscle groups
are specified, and a link to an animation is provided, which depicts how the
exercise is performed. The list exercises in the domain ontology is a subset of
exercises published at ExRx.net1.
1 ExRx (Exercise Prescription) on the Internet http://www.exrx.net</p>
        <p>The second component is the user specific ontology, which mimics the domain
ontology, but contains only those exercises that have been added to the system
during the search process. Initially, the list of exercises in this ontology is empty.</p>
        <p>
          Finally, the third component of the system’s knowledge base is the DBpedia
ontology [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ]. For performance reasons, in our demo this ontology contains a
subset of DBpedia derived from the seed concepts “physical exercise” and “physical
therapy” and all related entities to the 2nd degree. The subset of the DBpedia
ontology consists of 4375 entities.
3.2
        </p>
      </sec>
      <sec id="sec-3-2">
        <title>Demo Application</title>
        <p>To demonstrate the approach of the ontology-supported exploratory search,
we have implemented an application for the use case described above. The
whole interface is implemented as a Web application. At first, the user can
choose available information sources such as Web search APIs, local sources, and
ontologies. Furthermore, a color legend specifies possible annotations and their
corresponding ontologies.</p>
        <p>A schematic illustration of the main search interface is given in Figure 1. The
search field is placed at the top. While typing the search query, the system provides
suggestions based on the available ontologies. When the query is submitted, the
system triggers search in all chosen information sources. Search results retrieved
from the ontologies are shown directly below the search input. Here the title and
the corresponding super concept of an entity, e.g. for a physical exercise or a
DBpedia entity, is shown. On mouse over, a tool-tip with further information
such as preparation and execution of the exercise or a general description of the
DBpedia entity is faded in.</p>
        <p>Web search results are presented in the center of the interface. Each result is
accompanied with a title, summarizing text, URL, Web page thumbnail, and a
list of annotations. Annotations indicate terms that appear in the content of the
Web page and as a concept in one of the ontologies. The annotations are colored
in accordance with ontologies, where the concept appears. By hovering over an
annotation, the word and its surrounding context on the Web page is shown.
search input
research
context
search
results
and related
concepts from
all ontologies</p>
        <p>keyword</p>
        <sec id="sec-3-2-1">
          <title>Personal Ontology</title>
        </sec>
        <sec id="sec-3-2-2">
          <title>Exercise Ontology</title>
        </sec>
        <sec id="sec-3-2-3">
          <title>DBpedia</title>
        </sec>
        <sec id="sec-3-2-4">
          <title>Result Title</title>
          <p>Relevant text snippets
from each website
according to keywords</p>
        </sec>
        <sec id="sec-3-2-5">
          <title>Relevant Concepts</title>
          <p>Related Exercise
DBPedia Article</p>
        </sec>
        <sec id="sec-3-2-6">
          <title>Preview</title>
        </sec>
        <sec id="sec-3-2-7">
          <title>Image</title>
          <p>When a Web page is opened, the user can select and transfer information
about a relevant physical exercise from the page’s content to the system in order
to check whether the exercise is already present in one of the ontologies. If the
retrieved exercise is new, the user can add it to the personal ontology, e.g. to
complete the personal training plan.
4</p>
        </sec>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Conclusions and Future Work</title>
      <p>Domain ontologies are a helpful means to support users during a Web search
in a specific context. In this work, we presented an approach to search in
several information sources, such as ontologies and the Web, simultaneously. For
demonstration we have chosen a use case where a user searches for physical
training exercises to complete a personal training plan. For future work, a user
study to analyze the usage of the different information sources and the process of
information extraction can reveal new insights. Furthermore, it is interesting to
investigate different methods of extension of the initial domain-specific ontology
with information from the search results.</p>
    </sec>
    <sec id="sec-5">
      <title>Acknowledgments</title>
      <p>This work was done within the Transregional Collaborative Research Centre
SFB/TRR 62 “A Companion-Technology for Cognitive Technical Systems”
funded by the German Research Foundation. We would like to thank the contributors
of ExRx.net for the permission to use a subset of the published exercise library.</p>
    </sec>
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