What is Semantic Similarity? Definition of Semantic Similarity: A concept whereby a set of documents or terms within term lists are assigned a metric based on the likeness of their meaning/semantic content. ( Wikipedia, 2012e ).
- Dias, G. & Alves, E. (2005). Language-Independent Informative Topic Segmentation. In Proceedings of the 9th International Symposium on Social Communication. Santiago de Cuba, Cuba, January 24-28. pp. 588-592. ISBN: 9597174057. [pdf]
A. Abdulameer, H. M., S. Alrazak, and S. Lu. IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII):
475-485(October 2018)1. Chalom, Edmond, Eran Asa, and Elior Biton. "Measuring image similarity: an overview of some useful applications." IEEE Instrumentation & Measurement Magazine 16.1 (2013): 24-28. 2. Chandler, Damon M. "Seven challenges in image quality assessment: past, present, and future research." ISRN Signal Processing 2013 (2013). 3. Chandler, Damon M., Md Mushfiqul Alam, and Thien D. Phan. "Seven challenges for image quality research." Human Vision and Electronic Imaging XIX. Vol. 9014. International Society for Optics and Photonics, 2014. 4. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Zernike moments for facial expression recognition." rn 2 (2009): 3. 5. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Higher order orthogonal moments for invariant facial expression recognition." Digital Signal Processing 20.6 (2010): 1771-1779. 6. Pass, Greg, and Ramin Zabih. "Comparing images using joint histograms." Multimedia systems 7.3 (1999): 234-240. 7. Shnain, Noor Abdalrazak, Zahir M. Hussain, and Song Feng Lu. Ä feature-based structural measure: An image similarity measure for face recognition." Applied Sciences 7.8 (2017): 786. 8. Wang, Zhou, et al. "Image quality assessment: from error visibility to structural similarity." IEEE transactions on image processing 13.4 (2004): 600-612. 9. Zhang, Lin, et al. "FSIM: a feature similarity index for image quality assessment." IEEE transactions on Image Processing20.8 (2011): 2378-2386. 10. Aljanabi, Mohammed Abdulameer, Zahir M. Hussain, and Song Feng Lu. Än entropy-histogram approach for image similarity and face recognition." Mathematical Problems in Engineering 2018 (2018). 11. Aljanabi, Mohammed Abdulameer, Noor Abdalrazak Shnain, and Song Feng Lu. Än image similarity measure based on joint histogram—Entropy for face recognition." Computer and Communications (ICCC), 2017 3rd IEEE International Conference on. IEEE, 2017. 12. Hwang, Sun-Kyoo, and Whoi-Yul Kim. Ä novel approach to the fast computation of Zernike moments." Pattern Recognition 39.11 (2006): 2065-2076. 13. Canny, John. Ä computational approach to edge detection." IEEE Transactions on pattern analysis and machine intelligence 6 (1986): 679-698. 14. Picard, C. F. "The use of information theory in the study of the diversity of biological populations." Proc. Fifth Berk. Symp. IV. 1979. 15. Ponomarenko, Nikolay, et al. "TID2008-a database for evaluation of full-reference visual quality assessment metrics." Advances of Modern Radioelectronics 10.4 (2009): 30-45. 16. Ninassi, A., P. Le Callet, and F. Autrusseau. "Subjective quality assessment-IVC database." online http://www. irccyn. ec-nantes. fr/ivcdb (2006). 17. “Laboratories, A.T. The Database of Faces,” http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 18. “FEI Face Database,” http://fei.edu.br/∼cet/facedatabase.html.
A. Budanitsky, and G. Hirst. Workshop on WordNet and Other Lexical Resources, Second meeting of the North American Chapter of the Association for Computational Linguistics, Pittsburgh, USA, (2001)