MALO-LSTM: Multimodal Sentiment Analysis Using Modified Ant Lion Optimization with Long Short Term Memory Network
Name of corresponding author: SRI RAMAN KOTHURI
I Sri Raman Kothuri am pursing my PhD studies in Department of Computer Science and Engineering, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, India.
1. My first research article mentioned earlier is based on filing the research gap between emotion recognition as is sentimental analysis and Indian Carnatic music recommendation.
For most the main question of multimodal techniques in existing works, here is my justification as
1. The existing works of seo , poria , Angadi  and kwon are involved in any two modals( textual/video/audio) of multiple modalities and/or subjective to their problem statement consent of adapting approaches. Here in my work, I had used LSTM approach in Modified Ant Lion optimizer which is novel and nowhere literature it is reference as par my knowledge and work progress.
2. And my work of selection of music emotion at output layer is based on hyper parametrial achievement in sensitivity and classification accuracy that is truely observed in specific environment on machine I worked on and the same result I mentioned without conjugating their works that is improvement in accuracy and sensitivity results if hyper parametrial optimal selection approach using LSTM ( Novelty) in MALO algorithm( specified) in works.
3. Oflate I assure you that the configuration of LSTM deep networks is completely novel unlike existing method specified in previous works.
4. I shall also convey that it is continuation of my previous work where I did hybrid subset feature selection of incremental wrapper nature with Shuffled frog leaping algorithm in sentimental analysis which leads to this accurate classification of Carnatic raga/music recommendation/identification as my moto and was achieved in thorough process of this current work, proposed in this article.
5. Since it is my Ph.D degree research work I have taken care of NO self-citation by discretizing objective as next level context and submitted the result of the same.