Utilizing Knowledge Graphs for Text-Centric Information Retrieval

The past decade has witnessed the emergence of several publicly available and proprietary knowledge graphs (KGs). The depth and breadth of content in these KGs made them not only rich sources of structured knowledge by themselves, but also valuable resources for search systems. A surge of recent developments in entity linking and entity retrieval methods gave rise to a new line of research that aims at utilizing KGs for text-centric retrieval applications. This tutorial is the first to summarize and disseminate the progress in this emerging area to industry practitioners and researchers.

  • [DOI] L. Dietz, A. Kotov, and E. Meij, “Utilizing knowledge graphs for text-centric information retrieval,” in The 41st international acm sigir conference on research & development in information retrieval, New York, NY, USA, 2018, p. 1387–1390.
    [Bibtex]
    @inproceedings{SIGIR:2018:Dietz-Tut,
    Acmid = {3210187},
    Address = {New York, NY, USA},
    Author = {Dietz, Laura and Kotov, Alexander and Meij, Edgar},
    Booktitle = {The 41st International ACM SIGIR Conference on Research \& Development in Information Retrieval},
    Date-Added = {2018-07-26 18:24:31 +0000},
    Date-Modified = {2018-07-26 18:31:50 +0000},
    Doi = {10.1145/3209978.3210187},
    Isbn = {978-1-4503-5657-2},
    Keywords = {entity linking, entity retrieval, information retrieval, knowledge graphs},
    Location = {Ann Arbor, MI, USA},
    Numpages = {4},
    Pages = {1387--1390},
    Publisher = {ACM},
    Series = {SIGIR '18},
    Title = {Utilizing Knowledge Graphs for Text-Centric Information Retrieval},
    Url = {http://doi.acm.org/10.1145/3209978.3210187},
    Year = {2018},
    Bdsk-Url-1 = {http://doi.acm.org/10.1145/3209978.3210187},
    Bdsk-Url-2 = {https://doi.org/10.1145/3209978.3210187}}

Overview of The First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis (KG4IR)

Knowledge graphs have been used throughout the history of information retrieval for a variety of tasks. Advances in knowledge acquisition and alignment technology in the last few years have given rise to a body of new approaches for utilizing knowledge graphs in text retrieval tasks. This report presents the motivation, output, and outlook of the first workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis which was co-located with SIGIR 2017 in Tokyo, Japan. We aim to assess where we stand today, what future directions are, and which preconditions could lead to further performance increases.

  • [DOI] L. Dietz, C. Xiong, and E. Meij, “Overview of the first workshop on knowledge graphs and semantics for text retrieval and analysis (kg4ir),” Sigir forum, vol. 51, iss. 3, p. 139–144, 2018.
    [Bibtex]
    @article{Forum:2018:Dietz,
    Acmid = {3190601},
    Address = {New York, NY, USA},
    Author = {Dietz, Laura and Xiong, Chenyan and Meij, Edgar},
    Date-Added = {2018-07-26 18:22:37 +0000},
    Date-Modified = {2018-07-26 18:22:48 +0000},
    Doi = {10.1145/3190580.3190601},
    Issn = {0163-5840},
    Issue_Date = {December 2017},
    Journal = {SIGIR Forum},
    Month = 2,
    Number = {3},
    Numpages = {6},
    Pages = {139--144},
    Publisher = {ACM},
    Title = {Overview of The First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis (KG4IR)},
    Url = {http://doi.acm.org/10.1145/3190580.3190601},
    Volume = {51},
    Year = {2018},
    Bdsk-Url-1 = {http://doi.acm.org/10.1145/3190580.3190601},
    Bdsk-Url-2 = {https://doi.org/10.1145/3190580.3190601}}

The First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis (KG4IR)

Knowledge graphs have been used throughout the history of information retrieval for a variety of tasks. Advances in knowledge acquisition and alignment technology in the last few years have given rise to a body of new approaches for utilizing knowledge graphs in text retrieval tasks. This report presents the motivation, output, and outlook of the first workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis which was co-located with SIGIR 2017 in Tokyo, Japan. We aim to assess where we stand today, what future directions are, and which preconditions could lead to further performance increases. See https://kg4ir.github.io/ for more info.

  • [DOI] L. Dietz, C. Xiong, and E. Meij, “The first workshop on knowledge graphs and semantics for text retrieval and analysis (kg4ir),” in Proceedings of the 40th international acm sigir conference on research and development in information retrieval, New York, NY, USA, 2017, p. 1427–1428.
    [Bibtex]
    @inproceedings{SIGIR:2017:Dietz,
    Acmid = {3084371},
    Address = {New York, NY, USA},
    Author = {Dietz, Laura and Xiong, Chenyan and Meij, Edgar},
    Booktitle = {Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval},
    Date-Added = {2018-07-26 18:17:39 +0000},
    Date-Modified = {2018-07-26 18:17:51 +0000},
    Doi = {10.1145/3077136.3084371},
    Isbn = {978-1-4503-5022-8},
    Keywords = {entities, information retrieval, knowledge graphs},
    Location = {Shinjuku, Tokyo, Japan},
    Numpages = {2},
    Pages = {1427--1428},
    Publisher = {ACM},
    Series = {SIGIR '17},
    Title = {The First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis (KG4IR)},
    Url = {http://doi.acm.org/10.1145/3077136.3084371},
    Year = {2017},
    Bdsk-Url-1 = {http://doi.acm.org/10.1145/3077136.3084371},
    Bdsk-Url-2 = {https://doi.org/10.1145/3077136.3084371}}

Entity Linking and Retrieval for Semantic Search (WSDM 2014)

This morning, we presented the last edition of our tutorial series on Entity Linking and Retrieval, entitled “Entity Linking and Retrieval for Semantic Search” (with Krisztian Balog and Daan Odijk) at WSDM 2014! This final edition of the series builds upon our earlier tutorials at WWW 2013 and SIGIR 2013. The focus of this edition lies on the practical applications of Entity Linking and Retrieval, in particular for semantic search: more and more search engine users are expecting direct answers to their information needs (rather than just documents). Semantic search and its recent applications are enabling search engines to organize their wealth of information around entities. Entity linking and retrieval is at the basis of these developments, providing the building stones for organizing the web of entities.

This tutorial aims to cover all facets of semantic search from a unified point of view and connect real-world applications with results from scientific publications. We provide a comprehensive overview of entity linking and retrieval in the context of semantic search and thoroughly explore techniques for query understanding, entity-based retrieval and ranking on unstructured text, structured knowledge repositories, and a mixture of these. We point out the connections between published approaches and applications, and provide hands-on examples on real-world use cases and datasets.

As before, all our tutorial materials are available for free online, see http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/.