Submit your paper : editorIJETjournal@gmail.com Paper Title : RECOMMDATION OF INDIAN CUSINE RECIPIES BASED ON INGREDIENTS ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7239116 MLA Style: -Mrs.S.Kamala Harsha, Joshi Shravani, Guvvala Javeri Laxmipriya RECOMMDATION OF INDIAN CUSINE RECIPIES BASED ON INGREDIENTS , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -Mrs.S.Kamala Harsha, Joshi Shravani, Guvvala Javeri Laxmipriya RECOMMDATION OF INDIAN CUSINE RECIPIES BASED ON INGREDIENTS , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract The Recipe Recommendation Program for Indian Cuisines is a program that learns from the past tastes of a user's favorite recipes to recommend a fresh, untested cuisine. The basis of the recommendation is the ingredients that the user has already liked in the recipes India's traditional cuisine has been largely refreshing owing to its impressive use of herbs and tastes. Indian cuisine is renowned for its broad variety of dishes. The cooking style moves from the city to the district and is usually divided into South Indian and North Indian cuisine. India is very much praised for its variety of multi-foods accessible in various and inn resorts, suggestive of unity in a number of ways. The staple food in India involves maize, rice, and chana (Bengal Gram) heartbeats that are the most important. At present, there has been a great deal of improvement in the Indian sense of taste. Bengali cuisine is exciting because of its excellent usage of panch phoron, a word used to apply to the five essential flavor's, to be a common mustard. Fenugreek seed, cumin seed, aniseed seed, and black cumin crop. Likewise, other dishes from all over the world are a mix of flavors that nourish taste buds. Reference [1] Wang, Haoyu, et al. (2018) "A Stock Secommendation System Using with Distributed Graph Computation and Trust Model-Collaborative Filtering Algorithm." 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC). IEEE) [2] Thakkar, Priyank, et al. "Combining User-Based and Item-Based Collaborative Filtering Using Machine Learning." Information and Communication Technology for Intelligent Systems. Springer, Singapore, 2019. 173-180. [3] Pereira, Nymphia, and Satishkumar L. Varma. "Financial Planning Recommendation System Using Content-Based Collaborative and Demographic Filtering." Smart Innovations in Communication and Computational Sciences. Springer, Singapore, 2019. 141-151. [4] Pereira, Nymphia, and Satishkumar L. Varma. "Financial Planning Recommendation System Using Content-Based Collaborative and Demographic Filtering."Smart Innovations in Communication and Computational Sciences. Springer, Singapore, 2019. 141-151. [5] Qian, Yongfeng, et al. "EARS: Emotion-aware recommender system based on hybrid information fusion." Information Fusion 46 (2019): 141-146. [6] Kolla, Bhanu Prakash, and Arun Raja Raman. "Data Engineered Content Extraction Studies for Indian Web Pages." Computational Intelligence in Data Mining. Springer, Singapore, 2019. 505-512 [7] Patel, Ankit Dilip, and Yogesh Kumar Sharma. "Web Page Classification on News Feeds Using Hybrid Technique for Extraction."Information and Communication Technology for Intelligent Systems. Springer, Singapore, 2019. 399-405. [8] Goswami, Saptarsi, et al. "A review on application of data mining techniques to combat natural disasters." Ain Shams Engineering Journal 9.3 (2018): 365-378. [9] Zhao, Rui, and Kezhi Mao. "Fuzzy bag-of-words model for document representation."IEEE Transactions on Fuzzy Systems26.2 (2018): 794-804. [10] Sang, Jitao, Ming Yan, and Changsheng Xu. "Understanding Dynamic Cross-OSN Associations for Cold-start Recommendation." IEEE Transactions on Multimedia(2018). [11] Khan, Sadik, Yashpal Singh, and Kalpana Sharma. "Role of Web Usage Mining Technique for Website Structure Redesign."International Journal of Scientific Research in Computer Science, Engineering and Information Technology3.1 (2018). [12] Logesh, R., and V. Subramaniyaswamy. "Exploring Hybrid Recommender Recommendation of Indian Cuisine recipes based on Ingredients 2022 DepartmentofIT,MRECW Page52 Systems for Personalized Travel Applications."Cognitive Informatics and Soft Computing. Springer, Singapore, 2019. 535-544. [13] Sun, Y., Fang, M. and Wang, X., 2018. A novel stock recommendation system using Guba sentiment analysis. Personal and Ubiquitous Computing, 22(3), pp. 575-587. Keywords — RECOMMDATION OF INDIAN CUSINE RECIPIES BASED ON INGREDIENTS |