Abstract
Web page recommendation is one of the vital strategies in the era of Web 3.0 due to the exponential increase of the contents over the World Wide Web (WWW). In this paper CIPWR framework for recommendation of web pages which incorporates upper ontology generation, ontology alignment using the Lin similarity with an appropriate threshold and SynSet generation has been put forth. The framework integrates two topic models or encopresis the concept of Bi-topic modelling with two distinct topic models namely the Latent Dirchlet Allocation (LDA) and Latent Semantic Indexing (LSI) for lateral enrichment of topics and also the NELL and YAGO knowledge stores are integrated for Query word enrichment which is further used for feature selection and a Random forest classifier which is a strong machine learning driven feature controlled classifier has been added for the classification of the dataset and semantic similarity is computed by amalgamating cosine similarity and Jaccard similarity with the differential thresholds in order to yield the best in class results of 97.81% of average accuracy, 96.18% of average precision, 99.43% of average recall, 97.78% of average F-measure and the lowest FDR of 0.04 has been accomplished by the proposed CIPWR framework.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Gopalakrishnan, T., Sengottuvelan, P., Bharathi, A., Lokeshkumar, R.: An approach to webpage prediction method using variable order Markov model in recommendation systems. J. Internet Technol. 19(2), 415–424 (2018)
Chawla, S.: Intelligent web search system for personalised web search based on recommendation of web page communities. Int. J. Intell. Syst. Des. Comput. 3(1), 12–30 (2019)
Rajani, L., Thakar, U.: Webpage recommendation for organization users via collaborative page weight. J. Sci. Res. 65(1), 230–236n (2021)
Chaipornkaew, P., Banditwattanawong, T.: A recommendation model based on user behaviors on commercial websites using TF-IDF, KMeans, and Apriori algorithms. In: Meesad, P., Sodsee, S., Jitsakul, W., Tangwannawit, S. (eds.) IC2IT 2021. LNNS, vol. 251, pp. 55–65. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79757-7_6
Singh, S., Aswal, M.S.: Constructing an effective ontology for web page recommendation. Int. J. Web Eng. Technol. 16(2), 86–112 (2021)
Cai, X., Han, J., Yang, L.: Generative adversarial network based heterogeneous bibliographic network representation for personalized citation recommendation. Proc. AAAI Conf. Artif. Intell. 32(1) (2018)
Surya, D., Deepak, G., Santhanavijayan, A.: KSTAR: a knowledge based approach for socially relevant term aggregation for web page recommendation. In: Motahhir, S., Bossoufi, B. (eds.) ICDTA 2021. LNNS, vol. 211, pp. 555–564. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73882-2_50
Chhatwal, G.S., Deepak, G.: IEESWPR: an integrative entity enrichment scheme for socially aware web page recommendation. In: Data Science and Security, pp. 239–249. Springer, Singapore (2022). https://doi.org/10.1007/978-981-19-2211-4_21
Anusuya, S., Mallika, N.M.: Web page recommendation system using bat optimization and weighted support vector machine algorithm for health care service. Int. J. Health Sci. II, 5296–5317 (2022)
Kumar, N., Gupta, M., Sharma, D., Ofori, I.: Technical job recommendation system using APIs and web crawling. Comput. Intell. Neurosci. 5, 1–11 (2022)
Bedi, P., Goyal, S.B., Rajawat, A.S., Shaw, R.N., Ghosh, A.: A framework for personalizing atypical web search sessions with concept-based user profiles using selective machine learning techniques. In: Bianchini, M., Piuri, V., Das, S., Shaw, R.N. (eds.) Advanced Computing and Intelligent Technologies. LNNS, vol. 218, pp. 279–291. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-2164-2_23
Tran, D.H.: Semantic Indexing and Retrieval of Web Pages in a Web Browser (2022)
Azad, H.K., Deepak, A., Chakraborty, C., Abhishek, K.: Improving query expansion using pseudo-relevant web knowledge for information retrieval. Pattern Recogn. Lett. 158, 148–156 (2022)
Deepak, G., Priyadarshini, J.S., Babu, M.H.: A differential semantic algorithm for query relevant web page recommendation. In: IEEE International Conference on Advances in Computer Applications (ICACA), pp. 44–49, October 2016
Roopak, N., Deepak, G.: OntoKnowNHS: ontology driven knowledge centric novel hybridised semantic scheme for image recommendation using knowledge graph. In: Villazón-Terrazas, B., Ortiz-RodrÃguez, F., Tiwari, S., Goyal, A., Jabbar, M.A. (eds.) KGSWC 2021. CCIS, vol. 1459, pp. 138–152. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91305-2_11
Ojha, R., Deepak, G.: Metadata driven semantically aware medical query expansion. In: Villazón-Terrazas, B., Ortiz-RodrÃguez, F., Tiwari, S., Goyal, A., Jabbar, M.A. (eds.) KGSWC 2021. CCIS, vol. 1459, pp. 223–233. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91305-2_17
Rithish, H., Deepak, G., Santhanavijayan, A.: Automated assessment of question quality on online community forums. In: Motahhir, S., Bossoufi, B. (eds.) ICDTA 2021. LNNS, vol. 211, pp. 791–800. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73882-2_72
Yethindra, D.N., Deepak, G.: A semantic approach for fashion recommendation using logistic regression and ontologies. In: Proceedings of the 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), pp. 1–6. IEEE, September 2021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Manoj Kumar, H.S., Deepak, G., Santhanavijayan, A. (2023). CIWPR: A Strategic Framework for Collective Intelligence Encompassment for Web Page Recommendation. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 715. Springer, Cham. https://doi.org/10.1007/978-3-031-35507-3_22
Download citation
DOI: https://doi.org/10.1007/978-3-031-35507-3_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-35506-6
Online ISBN: 978-3-031-35507-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)