Skip to main content
Log in

Entity linking and API resource-based matchmaking for Web APIs composition

  • Original Research Paper
  • Published:
Service Oriented Computing and Applications Aims and scope Submit manuscript

Abstract

Web APIs composition is still a challenging task. In the classical semantic composition approach, the matchmaking process uses ontologies to ensure semantic matching between inputs and outputs. In this paper, we address the composition of Web APIs based on entity linking of Web APIs to a given knowledge base (KB). We first consider the APIs resources that make up the main core of REST Web APIs. Then, we link both the API resource described in the OAS (Open API Specification) documents and the input/output attributes of Web API operations to entities of the given KB. Finally, we perform discovery and composition of Web APIs based on their related entities extracted from the KB. Our dependency graph realizes matchmaking based on identifying similar entities of the API resources and the attributes of the requested input and output parameters. Focusing on API resources reduces the space of searching for candidate operations. Moreover, extending the user query by related similar entities adds semantics to the matchmaking process in the KB context. Experiments on the developed prototype show the feasibility and the scalability of our proposed composition approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. https://swagger.io/docs/specification/about/.

  2. https://www.w3.org/RDF/.

  3. https://www.w3.org/TR/rdf-schema/.

  4. https://www.w3.org/OWL/.

  5. https://www.w3.org/TR/sparql11-query/.

  6. https://lod-cloud.net/.

  7. https://www.w3.org/TR/sparql11-query/.

  8. https://apis.guru/.

  9. https://lod-cloud.net/.

References

  1. Fielding RT, Taylor RN (2002) Principled design of the modern Web architecture. ACM Trans Int Technol 2(2):115–150. https://doi.org/10.1145/514183.514185

    Article  Google Scholar 

  2. Richardson L, Ruby S (2007) RESTful web services. O’Reilly, London

    Google Scholar 

  3. Maleshkova M, Pedrinaci C, Domingue J (2010) Investigating web APIs on the world wide web. In: Eighth IEEE European conference on web services, vol 2010, pp 107–114. https://doi.org/10.1109/ECOWS.2010.9

  4. Fensel DA, Simsek U, Angele K, Huaman E, Kärle E, Panasiuk O, Toma I, Umbrich J, Wahler A (2020) Knowledge graphs: methodology, tools and selected use cases. Knowledge Graphs

  5. Aidan H, Eva B, Michael C, Claudia D, Gerard DM, Claudio G, Sabrina K, Emilio LGJ, Roberto N, Sebastian N, Axel-Cyrille NN, Axel P, Rashid Sabbir M, Anisa R, Lukas S, Juan S, Steffen S, Antoine Z (2021) Knowledge graphs. ACM Comput Surv 54(4):37. https://doi.org/10.1145/3447772

    Article  Google Scholar 

  6. Martinez-Rodriguez J, Hogan A, Lopez-Arevalo I (2020) Information extraction meets the semantic web: a survey. Semantic Web 11(2):255–335

    Article  Google Scholar 

  7. Henry R-M, Aidan H, Barbara P (2020) Fine-grained entity linking. J Web Semant. https://doi.org/10.1016/j.websem.2020.100600

    Article  Google Scholar 

  8. Berners-Lee T, Hendler J, Lassila O (2001) The semantic web. Sci Am 284(5):34–43

    Article  Google Scholar 

  9. Harris S, Seaborne A, Prud’hommeaux E (2013) SPARQL 1.1 query language. W3C Recommendation. W3C

  10. Shubham G, Pedro S, Craig K, Aman G, Mohsen T, Maria M (2015) Karma: a system for mapping structured sources into the semantic web. Science 7540:430–434. https://doi.org/10.1007/978-3-662-46641-4_40

    Article  Google Scholar 

  11. Taheriyan M, Knoblock CA, Szekely PA, Luis AJ (2012) Semi-automatically modeling web APIs to create linked apis. In: Proceedings of the ESWC 2012 workshop on linked APIs

  12. Alarcon R, Wilde E (2022) From RESTful services to RDF: connecting the web and the semantic web. ArXiv, arXiv:abs/1006.2718

  13. Alarcon R, Saffie R, Bravo N, Cabello J (2015) REST web service description for graph-based service discovery. In: Proceedings of the 15th international conference on engineering the web in the big data Era-volume 9114 (ICWE 2015). Springer, Berlin, pp 461-478. https://doi.org/10.1007/978-3-319-19890-3_30

  14. Serrano D, Stroulia E, Lau D, Ng T (2017) Linked REST APIs: a middleware for semantic REST API integration. IEEE Int Conf Web Serv 2017:138–145. https://doi.org/10.1109/ICWS.2017.26

    Article  Google Scholar 

  15. Serrano D, Stroulia E (2020) Semantics-based API discovery, matching and composition with linked metadata. Serv Oriented Comput Appl 14(4):283–296. https://doi.org/10.1007/s11761-020-00301-1

    Article  Google Scholar 

  16. Shang-Pin MS-P, MaHsuan-Ju LM-JH (2020) Semantic restful service composition using task specification. Int J Softw Eng Knowl Eng 30(06):835–857. https://doi.org/10.1142/S0218194020400094

    Article  Google Scholar 

  17. Kallab L, Chbeir R, Mrissa M (2019) Automatic K-Resources Discovery for Hybrid Web Connected Environments. ICWS 2019:146–153

    Google Scholar 

  18. Cremaschi M, De Paoli F (2018) A practical approach to services composition through light semantic descriptions. In: Kritikos K, Plebani P, de Paoli F (eds) Service-oriented and cloud computing. ESOCC 2018. Lecture Notes in Computer Science, vol 11116. Springer, Cham. https://doi.org/10.1007/978-3-319-99819-0_10

  19. Rodríguez-Mier P, Pedrinaci C, Lama M, Mucientes M (2016) An integrated semantic web service discovery and composition framework. IEEE Trans Serv Comput 9(2016):537–550

    Article  Google Scholar 

  20. Lee Y-J (2015) Semantic-based web API composition for data mashups. J Inf Sci Eng 31(4):1233–1248

    MathSciNet  Google Scholar 

  21. Mouhoub ML, Grigori D, Manouvrier M (2015) LIDSEARCH: a SPARQL-driven framework for searching linked data and semantic web services. ESWC (Satellite Events) 2015:112–117

    Google Scholar 

  22. Paolucci M, Kawamura T, Payne TR, Sycara KP (2002) Semantic matching of web services capabilities. In: Proceedings of the first international semantic web conference on the semantic web (ISWC ’02). Springer, Berlin, pp 333–347

  23. Cong P, Guohua B (2018) Using tag based semantic annotation to empower client and REST service interaction. Science 2018:64–71. https://doi.org/10.5220/0006682500640071

    Article  Google Scholar 

  24. Peng C, Goswami P (2019) Meaningful integration of data from heterogeneous health services and home environment based on ontology. Sensors 19(8):1747

    Article  Google Scholar 

  25. Lisa E, Wolfram W (2016) Towards a definition of knowledge graphs (PDF). In: SEMANTiCS2016. Leipzig: joint proceedings of the posters and demos track of 12th international conference on semantic systems-SEMANTiCS2016 and 1st international workshop on semantic change and evolving semantics (SuCCESS16), vol 2016, pp 13–16

  26. Wu G, He Y, Hu X (2018) Entity linking: an issue to extract corresponding entity with knowledge base. IEEE Access 6:6220–6231. https://doi.org/10.1109/ACCESS.2017.2787787

    Article  Google Scholar 

  27. Färber M (2018) Which knowledge graph is best for me? Linked data quality of DBpedia, Freebase. Wikidata, and YAGO in a Nutshell, OpenCyc

  28. Lehmann J, Isele R, Jakob M, Jentzsch A, Kontokostas D, Mendes PN, Hellmann S, Morsey M, Kleef PV, Auer S, Bizer C (2015) DBpedia-a large-scale, multilingual knowledge base extracted from Wikipedia. Semant Web 6:167–195

    Article  Google Scholar 

  29. Boustil A, Maamri R, Sahnoun Z (2014) A semantic selection approach for composite web services using OWL-DL and rules. Serv Orient Comput Appl 8(3):221–238. https://doi.org/10.1007/s11761-013-0150-6

    Article  Google Scholar 

  30. Kopecky J, Gomadam K, Vitvar T (2008) hRESTS: an HTML microformat for describing RESTful web services. In: Proceedings of the IEEE-WIC-ACM international conference on web intelligence (WI-IAT), pp 619–625. https://doi.org/10.1109/WIIAT.2008.379

  31. Verborgh R, Steiner T, Deursen DV, Walle RVd, Vallés JG (2011) Efficient runtime service discovery and consumption with hyperlinked RESTdesc. In: 7th international conference on next generation web services practices, Salamanca, vol 2011, pp 373–379, https://doi.org/10.1109/NWeSP.2011.6088208

  32. Musyaffa FA, Halilaj L, Siebes R, Orlandi F, Auer S (2016) Minimally invasive semantification of light weight service descriptions. In: Proceedings-2016 IEEE international conference on web services, ICWS 2016, pp 672–677. [7558066] Institute of Electrical and Electronics Engineers, Inc. https://doi.org/10.1109/ICWS.2016.93

  33. Michel F, Faron-Zucker C, Corby O, Gandon F (2019) Enabling automatic discovery and querying of Web APIs at web scale using linked data standards. In: Companion proceedings of the 2019 world wide web conference (WWW ’19). Association for Computing Machinery, New York, NY, USA, pp 883–892. https://doi.org/10.1145/3308560.3317073

  34. Dojchinovski M, Vitvar T (2017) Linked web APIs dataset: web APIs meet linked data. Semant Web 9(1–11):2017. https://doi.org/10.3233/SW-170259

    Article  Google Scholar 

  35. Svetlana O, Peep K (2015) A linked data model for web API-s. Science 2015:48–63. https://doi.org/10.1007/978-3-319-21915-8_4

    Article  Google Scholar 

  36. John D, Rajasree MS (2013) RESTDoc: describe, discover and compose RESTful semantic web services using annotated documentations. Int J Web Semant Technol 4:37–49. https://doi.org/10.5121/ijwest.2013.4103

    Article  Google Scholar 

  37. Pautasso C (2009) RESTful web service composition with BPEL for REST. J Data Knowl Eng 68(9):851–866

    Article  Google Scholar 

  38. Hamza HE, Izquierdo C, Cabot JJ (2018) APIComposer: data-driven composition of REST APIs: 7th IFIP WG 2.14 European conference, ESOCC 2018, Italy, September 12–14, 2018, Proceedings. https://doi.org/10.1007/978-3-319-99819-0_12

  39. Bennara M, Mrissa M, Amghar Y (2016) Semantic-enabled and hypermedia-driven linked service discovery. MEDI 2016:108–117. https://doi.org/10.1007/978-3-319-45547-1_9

    Article  Google Scholar 

  40. Bennara M, Amghar Y, Mrissa M (2015) Managing web resource compositions. WETICE 2015:176–181

    Google Scholar 

  41. García JM, Ruiz D, Ruiz-Cortés A (2012) Improving semantic web services discovery using SPARQL-based repository filtering. J Web Semant 17(2012):12–24. https://doi.org/10.1016/j.websem.2012.07.002

    Article  Google Scholar 

  42. Lanthaler M, Gütl C (2013) Hydra: a vocabulary for hypermedia-driven web APIs. In: Proceedings of the 6th workshop on linked data on the web (LDOW2013) at the 22nd international world wide web conference (WWW2013)

  43. Julien A-D, Hala S-M, Pascal M (2021) Processing SPARQL property path queries online with web preemption. In: The semantic web: 18th international conference, ESWC (2021) Virtual Event, June 6–10, 2021, proceedings. Springer, Berlin, pp 57–72. https://doi.org/10.1007/978-3-030-77385-4_4/

  44. Ramlee MN, Admodisastro N, Ali NM, Azrifah M (2019) A review of QOS-AWARE web service composition using metaheuristics approach. Int J Adv Sci Technol 28(2):308–314

  45. Mountantonakis M (2021) Large scale services for connecting and integrating hundreds of linked datasets. SIGWEB Newsl Autumn https://doi.org/10.1145/3494825:3494828

Download references

Funding

The authors certify that they have no funding was received for conducting this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Amel Boustil.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest with any person(s) or Organization(s).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Boustil, A., Tabet, Y. Entity linking and API resource-based matchmaking for Web APIs composition. SOCA 17, 93–108 (2023). https://doi.org/10.1007/s11761-022-00353-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11761-022-00353-5

Keywords

Navigation