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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Editorial for the 8th Bibliometric-enhanced Information Retrieval Workshop at ECIR 2019</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Motivation</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Relevance to ECIR</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Institute for Research in Applicable Computing, University of Bedfordshire</institution>
          ,
          <addr-line>Luton</addr-line>
          ,
          <country country="UK">UK</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Leibniz-Institute for the Social Sciences</institution>
          ,
          <addr-line>Cologne</addr-line>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>University of Toulouse, Computer Science Department</institution>
          ,
          <addr-line>IRIT UMR 5505</addr-line>
          ,
          <country country="FR">France</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2019</year>
      </pub-date>
      <abstract>
        <p>The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackles issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a hot topic investigated by both academia (e.g., ArnetMiner, CiteSeer , DocEar) and the industry (e.g., Google Scholar, Microsoft Academic Search, Semantic Scholar). This editorial presents the 8th iteration of the oneday BIR workshop held at ECIR 2019 in Cologne, Germany.</p>
      </abstract>
      <kwd-group>
        <kwd>Academic Search</kwd>
        <kwd>Information Retrieval</kwd>
        <kwd>Digital Libraries</kwd>
        <kwd>Bibliometrics</kwd>
        <kwd>Scientometrics</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        Bibliometric-enhanced IR systems must deal with the multifaceted nature
of scienti c information by searching for or recommending academic papers,
patents [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ], venues (i.e., conferences or journals), authors, experts (e.g., peer
reviewers), references (to be cited to support an argument), and datasets. The
underlying models harness relevance signals from keywords provided by authors,
topics extracted from the full-texts, coauthorship networks, citation networks,
and various classi cations schemes of science.
      </p>
      <p>
        Bibliometric-enhanced IR is a hot topic whose recent developments made
the news|see for instance the Initiative for Open Citations [
        <xref ref-type="bibr" rid="ref33">33</xref>
        ] and the Google
Dataset Search [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] launched on September 4, 2018. We believe that BIR@ECIR
is a much needed scienti c event for the retrievalists and citationists to meet and
join forces pushing the knowledge boundaries of IR applied to literature search
and recommendation.
2
      </p>
    </sec>
    <sec id="sec-2">
      <title>Past Related Activities</title>
      <p>
        The BIR workshop series was launched at ECIR in 2014 [
        <xref ref-type="bibr" rid="ref26">26</xref>
        ] and it was held
at ECIR each year since then [
        <xref ref-type="bibr" rid="ref20 ref21 ref22 ref25">25,20,21,22</xref>
        ]. As our workshop has been lying at
the crossroads between IR and NLP, we also ran it as a joint workshop called
BIRNDL (for Bibliometric-enhanced IR and NLP for Digital Libraries) at the
JCDL [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] and SIGIR [
        <xref ref-type="bibr" rid="ref18 ref19">18,19</xref>
        ] conferences. All workshops had a large number of
participants, demonstrating the relevance of the workshop's topics. The BIR
and BIRNDL workshop series gave the community the opportunity to discuss
latest developments and shared tasks such as the CL-SciSumm [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ], which was
introduced at the BIRNDL joint workshop.
      </p>
      <p>
        The authors of the most promising workshop papers were o ered the
opportunity to submit an extended version for a Special Issue for the Scientometrics
journal [
        <xref ref-type="bibr" rid="ref27 ref6">27,6</xref>
        ] and of the International Journal on Digital Libraries [
        <xref ref-type="bibr" rid="ref24">24</xref>
        ].
      </p>
      <p>The target audience of our workshop are researchers and practitioners, junior
and senior, from Scientometrics as well as Information Retrieval. These could
be IR researchers interested in potential new application areas for their work
as well as researchers and practitioners working with, for instance, bibliometric
data and interested in how IR methods can make use of such data.
3</p>
    </sec>
    <sec id="sec-3">
      <title>Objectives and Topics for BIR@ECIR 2019</title>
      <p>
        We called for original research at the crossroads of IR and Bibliometrics. Thirteen
peer-reviewed papers were accepted: 9 long papers, 3 short papers and 1 demo
paper. These report on new approaches using bibliometric clues to enhance the
search or recommendation of scienti c information or signi cant improvements
of existing techniques. Thorough quantitative studies of the various corpora to
be indexed (papers, patents, networks or else) were also contributed. The papers
are as follows:
Long papers:
{ An interactive visual tool for scienti c literature search: Proposal and
algorithmic speci cation [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]
{ A searchable space with routes for querying scienti c information [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ]
{ Discovering seminal works with marker papers [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ]
{ How do computer scientists use Google Scholar?: A survey of user interest
in elements on SERPs and author pro le pages [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ]
{ Feature selection and graph representation for an analysis of science elds
evolution: An application to the digital library ISTEX [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ]
{ Optimal citation con-text window sizes for biomedical retrieval [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ]
{ Bibliometric-enhanced arXiv: A data set for paper-based and citation-based
tasks [
        <xref ref-type="bibr" rid="ref30">30</xref>
        ]
{ Mining intellectual in uence associations [
        <xref ref-type="bibr" rid="ref32">32</xref>
        ]
{ Citation metrics for legal information retrieval systems [
        <xref ref-type="bibr" rid="ref40">40</xref>
        ]
Short papers:
Demo:
{ Finding temporal trends of scienti c concepts [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]
{ A preliminary study to compare deep learning with rule-based approaches
for citation classi cation [
        <xref ref-type="bibr" rid="ref28">28</xref>
        ]
{ Improving scienti c article visibility by neural title simpli cation [
        <xref ref-type="bibr" rid="ref34">34</xref>
        ]
{ Recommending multimedia educational resources on the MOVING
platform [
        <xref ref-type="bibr" rid="ref37">37</xref>
        ]
      </p>
      <p>The topics of the workshop are in line with those of the past BIR and
BIRNDL workshops (Fig. 1): a mixture of IR and Bibliometric concepts and
techniques. More speci cally, the call for papers featured current research issues
regarding three aspects of the search/recommendation process:
1. User needs and behaviour regarding scienti c information, such as:
{ Finding relevant papers/authors for a literature review;
{ Measuring the degree of plagiarism in a paper;
{ Identifying expert reviewers for a given submission;
{ Flagging predatory conferences and journals.
2. The characteristics of scienti c information:
{ Measuring the reliability of bibliographic libraries;
{ Spotting research trends and research fronts.
3. Academic search/recommendation systems:
{ Modelling the multifaceted nature of scienti c information;
{ Building test collections for reproducible BIR.</p>
    </sec>
    <sec id="sec-4">
      <title>Peer Review Process and Organization</title>
      <p>
        The 8th BIR edition ran as a one-day workshop, as it was the case for the previous
editions. Dr. Iana Atanassova delivered a keynote entitled "Beyond Metadata:
the New Challenges in Mining Scienti c Papers" [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ] to kick o the day.
      </p>
      <p>Two types of papers were presented: long papers (15-minute talks) and short
papers (5-minute talks). As the interactive session introduced last year was
generally acclaimed, we decided to organize a interactive session to close the
workshop. Two weeks earlier, we invited all registered attendees to demonstrate their
prototypes or pitch a poster during ash presentations (5 minutes). This was an
opportunity for our speakers to further discuss their work and for the public to
showcase their work too.</p>
      <p>We ran the workshop with peer review supported by EasyChair5. Each
submission was assigned to 2 to 3 reviewers, preferably at least one expert in IR
and one expert in Bibliometrics. The stronger submissions were accepted as
long papers while weaker ones were accepted as short papers, and demo. All
authors were instructed to revise their submission according to the reviewers'
reports. All accepted papers were included in the workshop proceedings hosted
at ceur-ws.org, an established open access repository with no author-processing
charges.</p>
      <sec id="sec-4-1">
        <title>5 https://easychair.org</title>
        <p>As a follow-up of the workshop, the co-chairs will write a report summing
up the main themes and discussions to SIGIR Forum [23, for instance] and
BCS Informer6, as a way to advertise our research topics as widely as possible
among the IR community. All authors are encouraged to submit an extended
version of their papers to the Special Issue of the Scientometrics journal launched
in Spring 2019.</p>
      </sec>
      <sec id="sec-4-2">
        <title>6 https://irsg.bcs.org/informer/</title>
      </sec>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Atanassova</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          :
          <article-title>Beyond metadata: the new challenges in mining scienti c papers</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>8</volume>
          {
          <fpage>13</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Bascur</surname>
            ,
            <given-names>J.P.</given-names>
          </string-name>
          , van Eck,
          <string-name>
            <given-names>N.J.</given-names>
            ,
            <surname>Waltman</surname>
          </string-name>
          ,
          <string-name>
            <surname>L.</surname>
          </string-name>
          :
          <article-title>An interactive visual tool for scienti c literature search: Proposal and algorithmic speci cation</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>76</volume>
          {
          <fpage>87</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Beel</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Langer</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gipp</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          , Nurnberger, A.:
          <article-title>The architecture and datasets of docears research paper recommender system</article-title>
          .
          <source>D-Lib Magazine</source>
          <volume>20</volume>
          (
          <issue>11</issue>
          /12) (
          <year>2014</year>
          ). https://doi.org/10.1045/november14-beel
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <surname>Bohannon</surname>
            ,
            <given-names>J.:</given-names>
          </string-name>
          <article-title>A computer program just ranked the most in uential brain scientists of the modern era</article-title>
          .
          <source>Science</source>
          (
          <year>2016</year>
          ). https://doi.org/10.1126/science.aal0371
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chandrasekaran</surname>
            ,
            <given-names>M.K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jaidka</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kan</surname>
            ,
            <given-names>M.Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Wolfram</surname>
            ,
            <given-names>D</given-names>
          </string-name>
          . (eds.):
          <source>BIRNDL'16: Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries co-located with the Joint Conference on Digital Libraries</source>
          , vol.
          <volume>1610</volume>
          .
          <string-name>
            <surname>CEUR-WS</surname>
          </string-name>
          , Aachen (
          <year>2016</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          :
          <article-title>Bibliometric-enhanced information retrieval:</article-title>
          <source>Preface. Scientometrics</source>
          <volume>116</volume>
          (
          <issue>2</issue>
          ),
          <volume>1225</volume>
          {
          <fpage>1227</fpage>
          (
          <year>2018</year>
          ). https://doi.org/10.1007/s11192-018-2861-0
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7.
          <string-name>
            <surname>Castelvecchi</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          :
          <article-title>Google unveils search engine for open data [News &amp; Comment]</article-title>
          .
          <source>Nature</source>
          (
          <year>2018</year>
          ). https://doi.org/10.1038/d41586-018-06201-x
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <surname>Fabre</surname>
            ,
            <given-names>R.:</given-names>
          </string-name>
          <article-title>A searchable space with routes for querying scienti c information</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>112</volume>
          {
          <fpage>124</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9. Farber,
          <string-name>
            <given-names>M.</given-names>
            ,
            <surname>Jatowt</surname>
          </string-name>
          ,
          <string-name>
            <surname>A.</surname>
          </string-name>
          :
          <article-title>Finding temporal trends of scienti c concepts</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>132</volume>
          {
          <fpage>139</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10. Gar eld, E.:
          <article-title>Citation indexes for science: A new dimension in documentation through association of ideas</article-title>
          .
          <source>Science</source>
          <volume>122</volume>
          (
          <issue>3159</issue>
          ),
          <volume>108</volume>
          {
          <fpage>111</fpage>
          (
          <year>1955</year>
          ). https://doi.org/10.1126/science.122.3159.108
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11. Gar eld, E.:
          <article-title>Patent citation indexing and the notions of novelty, similarity, and relevance</article-title>
          .
          <source>Journal of Chemical Documentation</source>
          <volume>6</volume>
          (
          <issue>2</issue>
          ),
          <volume>63</volume>
          {
          <fpage>65</fpage>
          (
          <year>1966</year>
          ). https://doi.org/10.1021/c160021a001
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <surname>Haunschild</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Marx</surname>
            ,
            <given-names>W.</given-names>
          </string-name>
          :
          <article-title>Discovering seminal works with marker papers</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>27</volume>
          {
          <fpage>38</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          13.
          <string-name>
            <surname>Jaidka</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chandrasekaran</surname>
            ,
            <given-names>M.K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Rustagi</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kan</surname>
          </string-name>
          , M.Y.:
          <article-title>Insights from CL-SciSumm 2016: The faceted scienti c document summarization shared task</article-title>
          .
          <source>International Journal on Digital Libraries</source>
          <volume>19</volume>
          (
          <issue>2</issue>
          {3),
          <volume>163</volume>
          {
          <fpage>171</fpage>
          (
          <year>2018</year>
          ). https://doi.org/10.1007/s00799-017-0221-y
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          14.
          <string-name>
            <surname>Kim</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Trippas</surname>
            ,
            <given-names>J.R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Sanderson</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Bao</surname>
            ,
            <given-names>Z.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Croft</surname>
          </string-name>
          , W.B.:
          <article-title>How do computer scientists use Google Scholar?: A survey of user interest in elements on SERPs and author pro le pages</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>64</volume>
          {
          <fpage>75</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          15.
          <string-name>
            <surname>Lamirel</surname>
            ,
            <given-names>J.C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cuxac</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          :
          <article-title>Feature selection and graph representation for an analysis of science elds evolution: An application to the digital library ISTEX</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>88</volume>
          {
          <fpage>99</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          16.
          <string-name>
            <surname>Leydesdor</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Milojevi</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          : Scientometrics. In: Wright,
          <string-name>
            <surname>J.D</surname>
          </string-name>
          . (ed.)
          <source>International Encyclopedia of the Social &amp; Behavioral Sciences</source>
          , vol.
          <volume>21</volume>
          , pp.
          <volume>322</volume>
          {
          <fpage>327</fpage>
          .
          <string-name>
            <surname>Elsevier</surname>
          </string-name>
          , 2nd edn. (
          <year>2015</year>
          ). https://doi.org/10.1016/b978-0
          <source>-08-097086-8</source>
          .
          <fpage>85030</fpage>
          -
          <lpage>8</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          17.
          <string-name>
            <given-names>Lykke</given-names>
            <surname>Nielsen</surname>
          </string-name>
          ,
          <string-name>
            <given-names>B.</given-names>
            ,
            <surname>Lavlund Skau</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            ,
            <surname>Meier</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            ,
            <surname>Larsen</surname>
          </string-name>
          ,
          <string-name>
            <surname>B.</surname>
          </string-name>
          :
          <article-title>Optimal citation context window sizes for biomedical retrieval</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>51</volume>
          {
          <fpage>63</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          18.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chandrasekaran</surname>
            ,
            <given-names>M.K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jaidka</surname>
            ,
            <given-names>K</given-names>
          </string-name>
          . (eds.):
          <source>BIRNDL'17: Proceedings of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries co-located with the Joint Conference on Digital Libraries</source>
          , vol.
          <year>1888</year>
          .
          <article-title>CEUR-WS, Aachen (</article-title>
          <year>2017</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          19.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chandrasekaran</surname>
            ,
            <given-names>M.K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jaidka</surname>
            ,
            <given-names>K</given-names>
          </string-name>
          . (eds.):
          <source>BIRNDL'17: Proceedings of the 3rd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries co-located with the Joint Conference on Digital Libraries</source>
          , vol.
          <volume>2132</volume>
          .
          <string-name>
            <surname>CEUR-WS</surname>
          </string-name>
          , Aachen (
          <year>2018</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          20.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G</given-names>
          </string-name>
          . (eds.):
          <source>BIR'16 Proceedings of the 3rd Workshop on Bibliometric-enhanced Information Retrieval co-located with the 38th European Conference on Information Retrieval</source>
          , vol.
          <volume>1567</volume>
          .
          <string-name>
            <surname>CEUR-WS</surname>
          </string-name>
          , Aachen (
          <year>2016</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation>
          21.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G</given-names>
          </string-name>
          . (eds.):
          <source>BIR'17 Proceedings of the 5th Workshop on Bibliometric-enhanced Information Retrieval co-located with the 39th European Conference on Information Retrieval</source>
          , vol.
          <year>1823</year>
          .
          <article-title>CEUR-WS, Aachen (</article-title>
          <year>2017</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref22">
        <mixed-citation>
          22.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G</given-names>
          </string-name>
          . (eds.):
          <source>BIR'18 Proceedings of the 7th Workshop on Bibliometric-enhanced Information Retrieval co-located with the 40th European Conference on Information Retrieval</source>
          , vol.
          <year>2080</year>
          .
          <article-title>CEUR-WS (</article-title>
          <year>2018</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref23">
        <mixed-citation>
          23.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          :
          <source>Report on the 7th International Workshop on Bibliometric-enhanced Information Retrieval (BIR</source>
          <year>2018</year>
          ).
          <source>SIGIR Forum</source>
          <volume>52</volume>
          (
          <issue>1</issue>
          ),
          <volume>135</volume>
          {
          <fpage>139</fpage>
          (
          <year>2018</year>
          ). https://doi.org/10.1145/3274784.3274798
        </mixed-citation>
      </ref>
      <ref id="ref24">
        <mixed-citation>
          24.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cabanac</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chandrasekaran</surname>
            ,
            <given-names>M.K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Jaidka</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kan</surname>
            ,
            <given-names>M.Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Wolfram</surname>
          </string-name>
          , D.:
          <article-title>Special issue on bibliometric-enhanced information retrieval and natural language processing for digital libraries</article-title>
          .
          <source>International Journal on Digital Libraries</source>
          <volume>19</volume>
          (
          <issue>2</issue>
          {3),
          <volume>107</volume>
          {
          <fpage>111</fpage>
          (
          <year>2018</year>
          ). https://doi.org/10.1007/s00799-017-0230-x
        </mixed-citation>
      </ref>
      <ref id="ref25">
        <mixed-citation>
          25.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Frommholz</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Mutschke</surname>
          </string-name>
          , P. (eds.):
          <source>BIR'15 Proceedings of the 2nd Workshop on Bibliometric-enhanced Information Retrieval co-located with the 37th European Conference on Information Retrieval</source>
          , vol.
          <volume>1344</volume>
          .
          <string-name>
            <surname>CEUR-WS</surname>
          </string-name>
          , Aachen (
          <year>2015</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref26">
        <mixed-citation>
          26.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Schaer</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Scharnhorst</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Larsen</surname>
            ,
            <given-names>B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Mutschke</surname>
          </string-name>
          , P. (eds.):
          <source>BIR'16 Proceedings of the 1st Workshop on Bibliometric-enhanced Information Retrieval co-located with the 36th European Conference on Information Retrieval</source>
          , vol.
          <volume>1143</volume>
          .
          <string-name>
            <surname>CEUR-WS</surname>
          </string-name>
          , Aachen (
          <year>2014</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref27">
        <mixed-citation>
          27.
          <string-name>
            <surname>Mayr</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Scharnhorst</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>Scientometrics and information retrieval: weak-links revitalized</article-title>
          .
          <source>Scientometrics</source>
          <volume>102</volume>
          (
          <issue>3</issue>
          ),
          <volume>2193</volume>
          {
          <fpage>2199</fpage>
          (
          <year>2015</year>
          ). https://doi.org/10.1007/s11192-014-1484-3
        </mixed-citation>
      </ref>
      <ref id="ref28">
        <mixed-citation>
          28.
          <string-name>
            <surname>Perier-Camby</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Bertin</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Atanassova</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Armetta</surname>
            ,
            <given-names>F.</given-names>
          </string-name>
          :
          <article-title>A preliminary study to compare deep learning with rule-based approaches for citation classi cation</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>125</volume>
          {
          <fpage>131</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref29">
        <mixed-citation>
          29.
          <string-name>
            <surname>Pritchard</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>Statistical bibliography or bibliometrics? [Documentation notes]</article-title>
          .
          <source>Journal of Documentation</source>
          <volume>25</volume>
          (
          <issue>4</issue>
          ),
          <volume>348</volume>
          {
          <fpage>349</fpage>
          (
          <year>1969</year>
          ). https://doi.org/10.1108/eb026482
        </mixed-citation>
      </ref>
      <ref id="ref30">
        <mixed-citation>
          30.
          <string-name>
            <surname>Saier</surname>
            ,
            <given-names>T.</given-names>
          </string-name>
          , Farber, M.:
          <article-title>Bibliometric-enhanced arXiv: A data set for paper-based and citation-based tasks</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>14</volume>
          {
          <fpage>26</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref31">
        <mixed-citation>
          31.
          <string-name>
            <surname>Salton</surname>
          </string-name>
          , G.:
          <article-title>Associative document retrieval techniques using bibliographic information</article-title>
          .
          <source>Journal of the ACM</source>
          <volume>10</volume>
          (
          <issue>4</issue>
          ),
          <volume>440457</volume>
          (
          <year>1963</year>
          ). https://doi.org/10.1145/321186.321188
        </mixed-citation>
      </ref>
      <ref id="ref32">
        <mixed-citation>
          32.
          <string-name>
            <surname>Shah</surname>
            ,
            <given-names>T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Pudi</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          :
          <article-title>Mining intellectual in uence associations</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>100</volume>
          {
          <fpage>111</fpage>
          . CEURWS.org (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref33">
        <mixed-citation>
          33.
          <string-name>
            <surname>Shotton</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          :
          <article-title>Funders should mandate open citations</article-title>
          .
          <source>Nature</source>
          <volume>553</volume>
          (
          <issue>7687</issue>
          ),
          <volume>129</volume>
          (
          <year>2018</year>
          ). https://doi.org/10.1038/d41586-018-00104-7
        </mixed-citation>
      </ref>
      <ref id="ref34">
        <mixed-citation>
          34.
          <string-name>
            <surname>Shvets</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>Improving scienti c article visibility by neural title simpli cation</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>140</volume>
          {
          <fpage>147</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref35">
        <mixed-citation>
          35.
          <string-name>
            <surname>Sinha</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Shen</surname>
            ,
            <given-names>Z.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Song</surname>
            ,
            <given-names>Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ma</surname>
          </string-name>
          , H.,
          <string-name>
            <surname>Eide</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Hsu</surname>
            ,
            <given-names>B.J.P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Wang</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          :
          <article-title>An overview of Microsoft Academic Service (MAS) and applications</article-title>
          . In: Gangemi,
          <string-name>
            <given-names>A.</given-names>
            ,
            <surname>Leonardi</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            ,
            <surname>Panconesi</surname>
          </string-name>
          ,
          <string-name>
            <surname>A</surname>
          </string-name>
          . (eds.)
          <source>WWW'15: Proceedings of the 24th International Conference on World Wide Web</source>
          . pp.
          <volume>243</volume>
          {
          <fpage>246</fpage>
          .
          <string-name>
            <surname>ACM</surname>
          </string-name>
          , New York, NY, USA (
          <year>2015</year>
          ). https://doi.org/10.1145/2740908.2742839
        </mixed-citation>
      </ref>
      <ref id="ref36">
        <mixed-citation>
          36.
          <string-name>
            <surname>Tang</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          , Zhang, J.,
          <string-name>
            <surname>Yao</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Li</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          , Zhang,
          <string-name>
            <given-names>L.</given-names>
            ,
            <surname>Su</surname>
          </string-name>
          ,
          <string-name>
            <surname>Z.</surname>
          </string-name>
          :
          <article-title>ArnetMiner: Extraction and mining of academic social networks</article-title>
          .
          <source>In: KDD'08:</source>
          <article-title>Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining</article-title>
          . pp.
          <volume>990</volume>
          {
          <fpage>998</fpage>
          .
          <string-name>
            <surname>ACM</surname>
          </string-name>
          , New York, NY, USA (
          <year>2008</year>
          ). https://doi.org/10.1145/1401890.1402008
        </mixed-citation>
      </ref>
      <ref id="ref37">
        <mixed-citation>
          37.
          <string-name>
            <surname>Vagliano</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Nazir</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          :
          <article-title>Recommending multimedia educational resources on the MOVING platform</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>148</volume>
          {
          <fpage>158</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref38">
        <mixed-citation>
          38.
          <string-name>
            <surname>Van</surname>
            <given-names>Noorden</given-names>
          </string-name>
          ,
          <string-name>
            <surname>R.</surname>
          </string-name>
          :
          <article-title>Google Scholar pioneer on search engines future</article-title>
          .
          <source>Nature</source>
          (
          <year>2014</year>
          ). https://doi.org/10.1038/nature.
          <year>2014</year>
          .16269
        </mixed-citation>
      </ref>
      <ref id="ref39">
        <mixed-citation>
          39.
          <string-name>
            <surname>White</surname>
            ,
            <given-names>H.D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>McCain</surname>
            ,
            <given-names>K.W.</given-names>
          </string-name>
          :
          <article-title>Visualizing a discipline: An author co-citation analysis of Information Science,</article-title>
          <year>1972</year>
          {
          <year>1995</year>
          .
          <source>Journal of the American Society for Information Science</source>
          <volume>49</volume>
          (
          <issue>4</issue>
          ),
          <volume>327</volume>
          {
          <fpage>355</fpage>
          (
          <year>1998</year>
          ). https://doi.org/b57vc7
        </mixed-citation>
      </ref>
      <ref id="ref40">
        <mixed-citation>
          40.
          <string-name>
            <surname>Wiggers</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Verberne</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          :
          <article-title>Citation metrics for legal information retrieval systems</article-title>
          .
          <source>In: Proc. of the 8th Workshop on Bibliometric-enhanced Information Retrieval</source>
          . pp.
          <volume>39</volume>
          {
          <fpage>50</fpage>
          .
          <string-name>
            <surname>CEUR-WS.org</surname>
          </string-name>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref41">
        <mixed-citation>
          41.
          <string-name>
            <surname>Williams</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Wu</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Choudhury</surname>
            ,
            <given-names>S.R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Khabsa</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Giles</surname>
            ,
            <given-names>C.L.</given-names>
          </string-name>
          :
          <article-title>Scholarly big data information extraction and integration in the CiteSeer digital library</article-title>
          .
          <source>In: ICDE'14: Proceedings of the 30th IEEE International Conference on Data Engineering Workshops</source>
          . pp.
          <volume>68</volume>
          {
          <fpage>73</fpage>
          .
          <string-name>
            <surname>IEEE</surname>
          </string-name>
          (
          <year>2014</year>
          ). https://doi.org/10.1109/icdew.
          <year>2014</year>
          .6818305
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>