There are some users who write fake (or non-real) reviews to elevate some 10 Fake Review Detection using or lower some popular quality. To Dr. J. P. 10 unpopular product’s business product’s Deep Learning maintain the quality of websites and provide genuine resources to the Singh customers an automated system is required which can filter the fake reviews as soon it appears on the product page. In this project a Recurrent Neural Network based deep learning approach would be used for detecting Fake reviews. A recommendation system keeps track of user profile and product description for recommending products to customers. Sometimes users buy products in 11 Product recommendation system a stepwise manner, where buying of one product follows the buying of other 11 for e-commerce: A deep learning products. This project first finds the sequences followed by customers while approach with attention model purchasing products using long short-term memory with attention Dr. J. P. mechanism and hence, recommend the next products to the customers. The Singh project also finds the time gap between the purchased product and recommendation of next sequential products. Low-quality answers are those answers which are unable to fetched any user Dr. J. P. votes (0 vote) or receive negative votes from the users. For example, the Singh answer in this figure receive 0 vote. Such answers are considered as answers. To filter these low-quality answers manually is a challenging task for site Identifying Low-quality answers moderators. So, the aim of the project is design an automated system that 12 in CQA site using Deep Learning 12 identify the low-quality answers as soon as they posted using the Deep Approach learning concept. This system helps to minimize the low-quality answers of the site. Prediction of Closed Questions on Currently approx 6% of questions are marked as on Stack Exchange. Closed Community Question answering This is happens due to several reasons such as duplicate question, off topic Dr.J. P. 13 13 sites using Deep Learning questions and etc. The aim of this project is to design a system based on deep Singh Approach learning approach that predicts whether a question is closed or not. In the situation of any emergency, several users asking help by mentioning location information in the text of tweets. For example, a tweet God “Omg. 14 14 help us. Resently in Puerto Rico an earthquake occured. (0).(0)” containing
10 10 Fake Review Detection using Deep Learning There are some users who write fake (or non-real) reviews to elevate some unpopular product’s business or lower some popular product’s quality. To maintain the quality of websites and provide genuine resources to the customers an automated system is required which can filter the fake reviews as soon it appears on the product page. In this project a Recurrent Neural Network based deep learning approach would be used for detecting Fake reviews. Dr. J. P. Singh 11 11 Product recommendation system for e-commerce: A deep learning approach with attention model A recommendation system keeps track of user profile and product description for recommending products to customers. Sometimes users buy products in a stepwise manner, where buying of one product follows the buying of other products. This project first finds the sequences followed by customers while purchasing products using long short-term memory with attention mechanism and hence, recommend the next products to the customers. The project also finds the time gap between the purchased product and recommendation of next sequential products. Dr. J. P. Singh 12 12 Identifying Low-quality answers in CQA site using Deep Learning Approach Low-quality answers are those answers which are unable to fetched any user votes (0 vote) or receive negative votes from the users. For example, the answer in this figure receive 0 vote. Such answers are considered as answers. To filter these low-quality answers manually is a challenging task for site moderators. So, the aim of the project is design an automated system that identify the low-quality answers as soon as they posted using the Deep learning concept. This system helps to minimize the low-quality answers of the site. Dr. J. P. Singh 13 13 Prediction of Closed Questions on Community Question answering sites using Deep Learning Approach Currently approx 6% of questions are marked as Closed on Stack Exchange. This is happens due to several reasons such as duplicate question, off topic questions and etc. The aim of this project is to design a system based on deep learning approach that predicts whether a question is closed or not. Dr.J. P. Singh 14 14 In the situation of any emergency, several users asking help by mentioning location information in the text of tweets. For example, a tweet “Omg. God help us. Resently in Puerto Rico an earthquake occured. (0).(0)” containing