Abstract
As the social media usage is expanding and people are using more and more platforms to share their stories through pictures, the use of image tags is becoming more relevant in the social media world. On social media. It is often seen that the option of tagging the images that are uploaded. Since image tagging is optional to the users, many images are posted untagged. Now the problem which arises is without image tags these images are hard to find. To overcome this issue many automatic tagging tools have been proposed. But image tagging requires precision and accuracy so that the images are tagged automatically based on the content in them. The proposed methodology uses Structural Topic Modelling and semantic similarity to tag the images and classify them into their respective categories.
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References
Zhou, N., Cheung, W.K., Qiu, G., Xue, X.: A hybrid probabilistic model for unified collaborative and content-based image tagging. IEEE Trans. Pattern Anal. Mach. Intell. 33(7), 1281–1294 (2010)
Qian, X., Hua, X.S., Tang, Y.Y., Mei, T.: Social image tagging with diverse semantics. IEEE Trans. Cybern. 44(12), 2493–2508 (2014)
Sharma, H., Hazrati, G., Bansal, J.C.: Spider monkey optimization algorithm. In: Bansal, J., Singh, P., Pal, N. (eds.) Evolutionary and Swarm Intelligence Algorithms. SCI, vol. 779, pp. 43–59. Springer, Cham (2019). Doi: https://doi.org/10.1007/978-3-319-91341-4_4
Gers, F.A., Schmidhuber, J., Cummins, F.: Learning to forget: Continual prediction with LSTM (1999)
Sundermeyer, M., Schlu¨ter, R., Ney, H.: LSTM neural networks for language modelling. In: Thirteenth Annual Conference of the International Speech Communication Association (2012)
Ma, X., Hovy, E.: End-to-end sequence labelling via bi-directional lstm-cnns-crf (2016). arXiv preprint arXiv:1603.01354
Wang, S., Jiang, J.: Learning natural language inference with LSTM (2015). arXiv preprint arXiv:1512.08849
Chen, Q., Zhu, X., Ling, Z., Wei, S., Jiang, H., Inkpen, D.: Enhanced lstm for natural language inference (2016)
Swami, V., Kumar, S., Jain, S.: An improved spider monkey optimization algorithm. In: Soft Computing: Theories and Applications, pp. 73–81. Springer, Singapore (2018)
Deepak, G., Gulzar, Z., Leema, A.A.: An intelligent system for modelling and evaluation of domain ontologies for Crystallography as a prospective domain with a focus on their retrieval. Computers & Electrical Engineering, 107604 (2021)
Roopak, N., Deepak, G.: OntoKnowNHS: ontology driven knowledge centric novel hybridised semantic scheme for image recommendation using knowledge graph. In: Iberoamerican Knowledge Graphs and Semantic Web Conference, pp. 138–152. n. In IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society (pp. 5657–5662). IEEE, November 2021
Ojha, R., Deepak, G.: Metadata driven semantically aware medical query expansion. In: Iberoamerican Knowledge Graphs and Semantic Web Conference, pp. 223–233. Springer, Cham (2021). Doi: https://doi.org/10.1007/978-3-030-91305-2_17
Deepak, Gerard, Gulzar, Z., Leema, A.A.: An intelligent system for modelling and evaluation of domain ontologies for Crystallography as a prospective domain with a focus on their retrieval (2021)
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, September 2021
Adithya, V., Deepak, G.: HBlogRec: A Hybridized Cognitive Knowledge Scheme for Blog Recommendation infusing XGBoosting and Semantic Intelligence, July 2021
Krishnan, N., Deepak, G.: Towards a Novel Framework for Trust Driven Web URL Recommendation Incorporating Semantic Alignment and Recur- rent Neural Network, May 2021
Sawarn, S., Deepak, G.: An Approach for Document Clustering Using Semantic Similarity and Whale Optimization. In: Musleh Al-Sartawi, A.M., Razzaque, A., Kamal, M.M. (eds.) EAMMIS 2021. Lecture Notes in Networks and Systems, vol 239, pp. 322–333. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77246-8_31
Krishnan, N., Deepak, G.: KnowSum: knowledge inclusive approach for text summarization using semantic alignment. In: 2021 7th International Conference on Web Research (ICWR), pp. 227–231 (2021)
Pushpa, C.N., Deepak, G., Kumar, A., T. J. and V. 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 (2020)
Adithya, V., Deepak, G.: OntoReq: an ontology focused collective knowledge approach for requirement traceability modelling. In: Musleh Al-Sartawi, A.M., Razzaque, A., Kamal, M.M. (eds) Artificial Intelligence Systems and the Internet of Things in the Digital Era. EAMMIS 2021. Lecture Notes in Networks and Systems, vol 239. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77246-8_34
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. Lecture Notes in Networks and Systems, vol 211. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73882-2_50
Vaish, K., Deepak, G., Santhanavijayan, A.: DSEORA: integration of deep learning and metaheuristics for web page recommendation based on search engine optimization ranking. In: Shetty, N.R., Patnaik, L.M., Nagaraj, H.C., Hamsavath, P.N., Nalini, N. (eds.) Emerging Research in Computing, Information, Communication and Applications. LNEE, vol. 790, pp. 873–883. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-1342-5_69
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Sawarn, S., Deepak, G. (2022). MASSTagger: Metadata Aware Semantic Strategy for Automatic Image Tagging. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-031-01942-5_43
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DOI: https://doi.org/10.1007/978-3-031-01942-5_43
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