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          <string-name>Omar Alonso Marti A. Hearst Jaap Kamps</string-name>
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      <abstract>
        <p>These proceedings contain the contributed papers of the First International Workshop on Graph Search and Beyond (GSB 2015), held at SIGIR 2015 in Santiago de Chile, on August 13, 2015. Modern Web data is highly structured in terms of entities and relations from large knowledge resources, geo-temporal references and social network structure, resulting in a massive multidimensional graph. This graph essentially uni es both the searcher and the information resources that played a fundamentally di erent role in traditional IR, and \Graph Search" o ers major new ways to access relevant information. Graph search a ects both query formulation (complex queries about entities and relations building on the searcher's context) as well as result exploration and discovery (slicing and dicing the information using the graph structure) in a completely personalized way. This new graph based approach introduces great opportunities, but also great challenges, in terms of data quality and data integration, user interface design, and privacy. We view the notion of \graph search" as searching information from your personal point of view (you are the query) over a highly structured and curated information space. This goes beyond the traditional two-term queries and ten blue links results that users are familiar with, requiring a highly interactive session covering both query formulation and result exploration. The workshop attracted a range of researchers working on this and related topics, and made concrete progress working together on one of the greatest challenges in the years to come. The workshop consisted of three main parts. First, four keynotes to help us frame the problem, and create a common understanding of the challenges: Rose Marie Philip (Facebook), Swee Lim (Linkedin), Doug Oard (Maryland), and Alex Wade (Microsoft Research). Second, a boaster and poster session with 6 papers selected by the program committee from 8 submissions (a 75% acceptance rate). Each paper was reviewed by at least two members of the program committee. Third, breakout groups on di erent aspects of exploiting graph search, with reports being discussed in the nal session. The papers represent the ideas and opinions of the authors who are trying to stimulate debate. It is the combination of these papers and the debate that will make the workshop a success! We thank the ACM and SIGIR for hosting this workshop, and Diane Kelly, Fernando Diaz and Diego Arroyuelo for their outstanding support in the organization. Thanks also go to the program committee, the authors of the papers, and all participants without whom there would be no workshop.</p>
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      <p>Overview Paper
Overview of Graph Search and Beyond : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Omar Alonso, Marti Hearst and Jaap Kamps
Invited Papers
Graph Search at LinkedIn : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Swee Lim
Good Uses for Crummy Knowledge Graphs : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Douglas Oard
Personalized Post Search at Facebook : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Rose Marie Philip
Overview of Microsoft Academic Graph : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Alex Wade
Contributed Papers
Tree-Map: A Visualization Tool for Large Data : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Mahipal Jadeja and Kesha Shah
Leveraging Metropolis-Hastings Algorithm on Graph-based Model for
Multimodal IR : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Serwah Sabetghadam, Mihai Lupu and Andreas Rauber
Fusion of Heterogeneous Information in Graph-Based Ranking for
Query-Biased Summarization : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Kotaro Sakamoto, Hideyuki Shibuki, Tatsunori Mori and Noriko Kando
Unilateral Jaccard Similarity Coe cient : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Julio Santisteban and Javier Tejada Carcamo
Information Retrieval Boosted by Category for Troubleshooting Search
System : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :</p>
      <p>Bin Tong, Toshihiko Yanase, Hiroaki Ozaki and Makoto Iwayama</p>
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    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          <string-name>
            <given-names>Random</given-names>
            <surname>Walk</surname>
          </string-name>
          and Feedback on Scholarly Network : : : : : : : : : : : : : : : : : : : : Yingying Yu,
          <source>Zhuoren Jiang and Xiaozhong Liu 1 5</source>
          <volume>6 7 8 9 14 19 23 28 33</volume>
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
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