Skip to main content
SpringerLink
Log in

IPR: Integrative Policy Recommendation Framework Based on Hybrid Semantics

  • Conference paper
  • First Online:
Knowledge Graphs and Semantic Web (KGSWC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1686))

Included in the following conference series:

  • 519 Accesses

Abstract

Policy recommendations aim to inform people who are faced with policy decisions on specific issues about how research and evidence can assist them in making the best decisions possible. This paper proposes an ontology-focused semantical driven integrative system for policy recommendation. The recommendation is user query-centric and uses Structural Topic Modelling to find topics that can be correlated. The semantic similarities are computed using Resnik and concept similarity methods to achieve ontology alignment, and for the alignment of principle classes, three models, normalized compression distance, Twitter semantic similarity, and Hiep’s Evenness Index, are used. The IPR achieves the best-in-class accuracy of 94.72% and precision of 93.14% for a wide range of recommendations over the other baseline models, making it an efficient and semantically compliant system for the policies recommendation.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Zhang, T., Liu, M., Ma, C., Tu, Z., Wang, Z.: A text mining based method for policy recommendation. In: 2021 IEEE International Conference on Services Computing (SCC), pp. 233–240. IEEE (2021)

    Google Scholar 

  2. Toninelli, A., Bradshaw, J., Kagal, L., Montanari, R.: Rule-based and ontology-based policies: toward a hybrid approach to control agents in pervasive environments. In: Proceedings of the Semantic Web and Policy Workshop (2005)

    Google Scholar 

  3. Santos, O.C., Boticario, J.G.: Requirements for semantic educational recommender systems in formal e-learning scenarios. Algorithms 4(2), 131–154 (2011)

    Article  Google Scholar 

  4. Chung, H., Kim, J.: An ontological approach for semantic modeling of curriculum and syllabus in higher education. Int. J. Inf. Educ. Technol. 6(5), 365 (2016)

    Google Scholar 

  5. Joshi, K., Joshi, K.P., Mittal, S.: A semantic approach for automating knowledge in policies of cyber insurance services. In: 2019 IEEE International Conference on Web Services (ICWS), pp. 33–40. IEEE (2019)

    Google Scholar 

  6. Ge, J., Qiu, Y.: Concept similarity matching based on semantic distance. In: 2008 Fourth International Conference on Semantics, Knowledge and Grid, pp. 380–383. IEEE (2008)

    Google Scholar 

  7. Lu, J., Shambour, Q., Xu, Y., Lin, Q., Zhang, G.: BizSeeker: a hybrid semantic recommendation system for personalized government-to-business e-services. Internet Research (2010)

    Google Scholar 

  8. Deepak, G., Ahmed, A., Skanda, B.: An intelligent inventive system for personalised webpage recommendation based on ontology semantics. Int. J. Intell. Syst. Technol. Appl. 18(1–2), 115–132 (2019)

    Google Scholar 

  9. Adithya, V., Deepak, G.: OntoReq: an ontology focused collective knowledge approach for requirement traceability modelling. In: Musleh, A.-S., Abdalmuttaleb, M.A., Razzaque, A., Kamal, M.M. (eds.) EAMMIS 2021. LNNS, vol. 239, pp. 358–370. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77246-8_34

  10. Ortiz-Rodriguez, F., Tiwari, S., Panchal, R., Medina-Quintero, J. M., Barrera, R.: MEXIN: multidialectal ontology supporting NLP approach to improve government electronic communication with the Mexican Ethnic Groups. In: DG. O 2022: The 23rd Annual International Conference on Digital Government Research, pp. 461–463 (2022)

    Google Scholar 

  11. Deepak, G., Priyadarshini, J.S., Babu, M.H.: A differential semantic algorithm for query relevant web page recommendation. In: 2016 IEEE International Conference on Advances in Computer Applications (ICACA), pp. 44–49. IEEE (2016)

    Google Scholar 

  12. Ortiz-Rodriguez, F., Medina-Quintero, J. M., Tiwari, S., Villanueva, V.: EGODO ontology: sharing, retrieving, and exchanging legal documentation across e-government. In: Futuristic Trends for Sustainable Development and Sustainable Ecosystems, pp. 261–276. IGI Global (2022)

    Google Scholar 

  13. Panchal, R., Swaminarayan, P., Tiwari, S., Ortiz-Rodriguez, F.: AISHE-Onto: a semantic model for public higher education universities. In: DG. O2021: The 22nd Annual International Conference on Digital Government Research, pp. 545–547 (2021)

    Google Scholar 

  14. Tiwari S., Garcia-Castro R.: A Systematic Review of Ontologies for the Water Domain. In: ISTE Book, ISBN 9781786307644, Wiley (2022)

    Google Scholar 

  15. Tiwari, S., Gaurav, D., Srivastava, A., Rai, C., Abhishek, K.: A preliminary study of knowledge graphs and their construction. In: Tavares, J.R.S., Chakrabarti, S., Bhattacharya, A., Ghatak, S. (eds.) Emerging Technologies in Data Mining and Information Security. LNNS, vol. 164, pp. 11–20. Springer, Singapore (2021). https://doi.org/10.1007/978-981-15-9774-9_2

  16. Yethindra, D.N., Deepak, G.: A semantic approach for fashion recommendation using logistic regression and ontologies. In: 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), pp. 1–6. IEEE (2021)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics, Birla Institute of Science and Technology, Pilani, India

    Divyanshu Singh

  2. Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India

    Gerard Deepak

Authors
  1. Divyanshu Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gerard Deepak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gerard Deepak .

Editor information

Editors and Affiliations

  1. EY wavespace/UNIR, Madrid, Spain

    Boris Villazón-Terrazas

  2. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Fernando Ortiz-Rodriguez

  3. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Sanju Tiwari

  4. University of Alcalá, Alcalá de Henares, Spain

    Miguel-Angel Sicilia

  5. Universidad Camilo José Cela, Madrid, Spain

    David Martín-Moncunill

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Singh, D., Deepak, G. (2022). IPR: Integrative Policy Recommendation Framework Based on Hybrid Semantics. In: Villazón-Terrazas, B., Ortiz-Rodriguez, F., Tiwari, S., Sicilia, MA., Martín-Moncunill, D. (eds) Knowledge Graphs and Semantic Web . KGSWC 2022. Communications in Computer and Information Science, vol 1686. Springer, Cham. https://doi.org/10.1007/978-3-031-21422-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-21422-6_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21421-9

  • Online ISBN: 978-3-031-21422-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation