Abstract
With the increasing amounts of image and multimedia content on the World Wide Web, it is quite essential to retrieve images with maximum relevance and minimum deviations from the search query. The traditional content-based Image Retrieval algorithms are not compliant with the evolving Semantic Web. In this paper, a framework for Web Image Recommendation has been proposed that hybridizes Adaptive Normalized Compression Distance and Adaptive Pointwise Mutual Information strategies with varied and differential thresholds. The proposed framework facilitates ontology modeling for canonically synonymous terms that serve as an intelligent training strategy for web image retrieval. The proposed strategy for web image recommendation is annotations based that uses the context information of the image rather than the image features. The proposed web image retrieval is initiated by the query and driven by capturing user intentions dynamically incorporating the strategic query expansion technique. An overall F-Measure of 96.17% has been achieved.
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References
Niu, W., Caverlee, J., Lu, H.: Neural personalized ranking for image recommendation. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, pp. 423–431, February 2018
He, T., Zhu, N., Xiong, G.X., Zhao, Z.R.: Collaborating filtering community image recommendation system based on scene. In ITM Web of Conferences, vol. 12, p. 04010. EDP Sciences (2017)
Giri, G.L., Deepak, G., Manjula, S.H., Venugopal, K.R.: OntoYield: a semantic approach for context-based ontology recommendation based on structure preservation. In: Proceedings of International Conference on Computational Intelligence and Data Engineering, pp. 265–275. Springer, Singapore (2018)
Sejal, D., Ganeshsingh, T., Venugopal, K.R., Iyengar, S.S., Patnaik, L.M.: ACSIR: ANOVA cosine similarity image recommendation in vertical search. Int. J. Multimed. Inf. Retr. 6(2), 143–154 (2017)
Rajendran, T., Gnanasekaran, T.: Multi level object relational similarity based image mining for improved image search using semantic ontology. Clust. Comput. 22(2), 3115–3122 (2019)
Kousalya, S., Thananmani, A.S.: Image mining-similar image retrieval using multi-feature extraction and content based image retrieval technique. Int. J. Adv. Res. Comput. Commun. Eng. 2(11), 4369–4372 (2013)
Maheshvari, U., Thanushkodi, K.: Content based fast image retrieval using hybrid optimization techniques. In: The Proceedings of the International Conference on the Recent Advancements in Materials, Journal of Chemical and Pharmaceutical Sciences, pp. 102–107 (2015)
Ma, Y., Wang, C., Jin, B.: A framework to normalize ontology representation for stable measurement. J. Comput. Inf. Sci. Eng. 15(4) (2015)
Deepak, G., Andrade, S.: OntoRec: a semantic approach for ontology driven web image search. In: Proceedings of the International Conference on Big Data and Knowledge Discovery (ICBK), pp. 157–166 (2016)
Bedi, P., Thukral, A., Banati, H.: Focused crawling of tagged web resources using ontology. Comput. Electr. Eng. 39(2), 613–628 (2013)
Shekhar, S., Singh, A., Agrawal, S.C.: An object centric image retrieval framework using multi-agent model for retrieving non-redundant web images. Int. J. Image Mining 1(1), 4–22 (2015)
Deepak, G., Priyadarshini, S.J.: Onto tagger: ontology focused image tagging system incorporating semantic deviation computing and strategic set expansion. Int. J. Comput. Sci. Bus. Inform. 16(1) (2016)
Wang, M., Li, H., Tao, D., Lu, K., Wu, X.: Multimodal graph-based reranking for web image search. IEEE Trans. Image Process. 21(11), 4649–4661 (2012)
Deepak, G., Priyadarshini, J.S.: A hybrid semantic algorithm for web image retrieval incorporating ontology classification and user-driven query expansion. In: Advances in Big Data and Cloud Computing, pp. 41–49. Springer, Singapore (2018)
Deepak, G., Santhanavijayan, A.: OntoBestFit: A Best-Fit Occurrence Estimation strategy for RDF driven faceted semantic search. Comput. Commun. 160, 284–298 (2020)
Pushpa, C.N., Deepak, G., Kumar, A., Thriveni, J., Venugopal, K.R.: OntoDisco: improving web service discovery by hybridization of ontology focused concept clustering and interface semantics. In 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pp. 1–5. IEEE, July 2020
Kumar, A., Deepak, G., Santhanavijayan, A.: HeTOnto: a novel approach for conceptualization, modeling, visualization, and formalization of domain centric ontologies for heat transfer. In: 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pp. 1–6. IEEE, July 2020
Deepak, G., Kasaraneni, D.: OntoCommerce: an ontology focused semantic framework for personalised product recommendation for user targeted e-commerce. Int. J. Comput. Aided Eng. Technol. 11(4–5), 449–466 (2019)
Gulzar, Z., Anny Leema, A., Deepak, G.: PCRS: personalized course recommender system based on hybrid approach. Procedia Comput. Sci. 125, 518–524 (2018)
Deepak, G., Teja, V., Santhanavijayan, A.: A novel firefly driven scheme for resume parsing and matching based on entity linking paradigm. J. Discrete Math. Sci. Cryptogr. 23(1), 157–165 (2020)
Haribabu, S., Sai Kumar, P.S., Padhy, S., Deepak, G., Santhanavijayan, A., Kumar, N.D.: A Novel Approach for Ontology Focused Inter- Domain Personalized Search based on Semantic Set Expansion. In: 2019 Fifteenth International Conference on Information Processing (ICINPRO), Bengaluru, India, pp. 1–5 (2019). https://doi.org/10.1109/ICInPro47689.2019.9092155.
Deepak, G., Naresh Kumar, G., Sai, V.S.N., Bharadwaj, Y., Santhanavijayan, A.: OntoQuest: An Ontological Strategy for Automatic Question Generation for e-assessment using Static and Dynamic Knowledge. In: 2019 Fifteenth International Conference on Information Processing (ICINPRO), pp. 1–6. IEEE (2019)
Santhanavijayan, A., Naresh Kumar, D., Deepak, G.: A semantic-aware strategy for automatic speech recognition incorporating deep learning models. In: Intelligent System Design, pp. 247–254. Springer, Singapore
Deepak, G., et al.: Design and evaluation of conceptual ontologies for electrochemistry as a domain. In: 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE (2019)
Deepak, G., Priyadarshini, J.S.: Personalized and Enhanced Hybridized Semantic Algorithm for web image retrieval incorporating ontology classification, strategic query expansion, and content-based analysis. Comput. Electr. Eng. 72, 14–25 (2018)
Kaushik, I.S., Deepak, G., Santhanavijayan, A.: QuantQueryEXP: a novel strategic approach for query expansion based on quantum computing principles. J. Discrete Math. Sci. Cryptogr. 23(2), 573–584 (2020)
Varghese, L., Deepak, G., Santhanavijayan, A.: An IoT analytics approach for weather forecasting using raspberry Pi 3 Model B+. In 2019 Fifteenth International Conference on Information Processing (ICINPRO), pp. 1–5. IEEE (2019)
Shreyas, K., Deepak, G., Santhanavijayan, A.: GenMOnto: a strategic domain ontology modelling approach for conceptualisation and evaluation of collective knowledge for mapping genomes. J. Stat. Manag. Syst. 23(2), 445–452 (2020)
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Deepak, G., Santhanavijayan, A. (2021). AnnotSemRec: An RDF Based Semantic Framework for Personalized Web Image Search. In: Abraham, A., Hanne, T., Castillo, O., Gandhi, N., Nogueira Rios, T., Hong, TP. (eds) Hybrid Intelligent Systems. HIS 2020. Advances in Intelligent Systems and Computing, vol 1375. Springer, Cham. https://doi.org/10.1007/978-3-030-73050-5_41
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