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Recent trends in knowledge graphs: theory and practice

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Abstract

With the extensive growth of data that has been joined with the thriving development of the Internet in this century, finding or getting valuable information and knowledge from these huge noisy data became harder. The Concept of Knowledge Graph (KG) is one of the concepts that has come into the public view as a result of this development. In addition, with that thriving development especially in the last two decades, the need to process and extract valuable information in a more efficient way is increased. KG presents a common framework for knowledge representation, based on the analysis and extraction of entities and relationships. Techniques for KG construction can extract information from either structured, unstructured or even semi-structured data sources, and finally organize the information into knowledge, represented in a graph. This paper presents a characterization of different types of KGs along with their construction approaches. It reviews the existing academia, industry and expert KG systems and discusses in detail about the features of it. A systematic review methodology has been followed to conduct the review. Several databases (Scopus, GS, WoS) and journals (SWJ, Applied Ontology, JWS) are analysed to collect the relevant study and filtered by using inclusion and exclusion criteria. This review includes the state-of-the-art, literature review, characterization of KGs, and the knowledge extraction techniques of KGs. In addition, this paper overviews the current KG applications, problems, and challenges as well as discuss the perspective of future research. The main aim of this paper is to analyse all existing KGs with their features, techniques, applications, problems, and challenges. To the best of our knowledge, such a characterization table among these most commonly used KGs has not been presented earlier.

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Notes

  1. https://www.blog.google/products/search/introducing-knowledge-graph-things-not/.

  2. https://developers.google.com/freebase.

  3. https://babelnet.org/.

  4. https://wiki.dbpedia.org/develop/datasets.

  5. https://wordnet.princeton.edu/.

  6. http://www.globalwordnet.org/AWN/.

  7. http://ling.uni-konstanz.de/pages/home/mousser/files/Arabicverbnet.php.

  8. https://queue.acm.org/detail.cfm?id=3332266.

  9. https://www.poolparty.biz/what-is-a-knowledge-graph.

  10. https://www.slideshare.net/phaase/getting-started-with-knowledge-graphs.

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Authors and Affiliations

  1. Universidad Autonoma de Tamaulipas, Ciudad Victoria, Mexico

    Sanju Tiwari

  2. Faculty of Computer Sciences and Engineering, Hodeidah University, Hodeidah, Yemen

    Fatima N. Al-Aswadi

  3. Dept of Computer Science and Engineering, Indian Institute of Technology, Delhi, India

    Devottam Gaurav

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  1. Sanju Tiwari
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  3. Devottam Gaurav
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Correspondence to Sanju Tiwari.

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Tiwari, S., Al-Aswadi, F.N. & Gaurav, D. Recent trends in knowledge graphs: theory and practice. Soft Comput 25, 8337–8355 (2021). https://doi.org/10.1007/s00500-021-05756-8

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