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
24 24 Fault-tolerant Coordination in Wireless Environment. Understanding principles of fault tolerance, coordination middleware and publish/subscribe system; Designing and implementing coordination middleware prototype, based on Raspberry Pi kit and Java. Incorporating fault tolerance functionality in middleware prototype; Demonstrating prototype’s working in testbed. Dr. Suddhasil De 25 25 Data Aggregation in Dense Network. This research-oriented project covers the following activities: Understanding principles of data aggregation; Reviewing existing data aggregation techniques in different networks; Performance analysis of existing approaches. Dr. Suddhasil De 26 26 Forest fire detection in Wireless Sensor Network Wireless sensor network consists of various sensor devices that sense environmental conditions such as temperature, pressure, humidity etc. WSN has gained world-wide attention for forest fire detection. Now a day’s forest fire is a very considerable problem of ecological system. It is very important to detect the fire as early as possible. Several major problems like global warming, soil pollution, land infertility arise due to forest fire. This project proposes a novel technique to detect epicenters of fire in forest and prevent the forest from damage. Sensors are deployed in forest area to measure a variety of phenomena including temperature, relative humidity, smoke and transmit those huge amounts of data through wireless communication to the server in Fire Fire office takes necessary actions to prevent spreading the fire from the epicenter of forest fire zone. Dr. Ditipriya Sinha 27 27 Intrusion Detection applying Machine Learning Approach The growing prevalence of network attack is a well-known problem which can impact the security of critical information for both individuals and enterprises. In this project we will implement real time intrusion detection technique applying machine learning approach. Dr. Ditipriya Sinha 28 28 Localization in Wireless Sensor Network Wireless Sensor Network (WSN) consists of a large number of sensors, which are deployed in large areas for providing variety of applications such as remote health monitoring, disaster management (forest fire) etc. If all the sensor nodes are GPS connected, it requires high cost for implementation. This project proposes a novel technique to detect the location of sensor nodes Dr. Ditipriya Sinha