Priyank Thakkar

Priyank Thakkar
Nirma University | NU · Institute of Technology

About

19
Publications
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1,040
Citations

Publications

Publications (19)
Article
It has always been a challenge to accurately forecast the behavior of a stock market due to its extremely non-linear and dynamic nature. Numerous studies have shown that technical indicators describing stocks in conjunction with machine learning models can serve as useful tools for forecasting in the stock market. There are various challenges, and...
Article
Full-text available
Traditional border surveillance technologies like surveillance tower may not always be feasible in hostile military area. Internet of Things (IoT) and Wireless Sensor Networks (WSN) has demonstrated great promise in serving applications like traffic monitoring, industrial process control, health care, surveillance etc. Using only scalar sensors suf...
Article
Full-text available
Predicting a stock's next day price is a challenging task that researchers have long been attempting to address. Machine learning algorithms have shown to be successful at predicting next day price of a stock. A single machine learning model, however, suffers from limited stability and predictive power. Parallel models bring together a diverse set...
Chapter
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With the worldwide growth in vehicles due to the increase in population, Vehicular ad hoc networks (VANETs) have attracted researchers both from academia as well as the industry. It provides a smart and efficient driving experience for drivers. Traditional VANET suffers from various issues of security, QoS, and latency. To address these problems, s...
Conference Paper
Speaker Diarization deals with determining “who spoke when?” with the help of computers. It is extremely useful in speech transcription, subtitle generation and extracting opinions among others. Diarization is a process in which a relatively long audio recording is processed and speech segments are labeled using respective speaker identities. Such...
Conference Paper
Due to miniaturization of hardware and availability of low-cost, low-power sensors, Wireless Sensor Network and Multimedia Sensor Network applications are increasing day by day. Each application has a specific quality of service and experience requirements. The design of routing and MAC protocol which can fulfill the requirements of the application...
Conference Paper
Collaborative Filtering (CF) is one of the most effective approaches to engineer recommendation systems. It recommends those items to user which other users with related preferences and tastes liked in the past. User-based and Item-based Collaborative Filtering (IbCF) are two flavours of collaborative filtering. Both of these methods are used to es...
Article
In modern times, it has become very essential for e-commerce businesses to empower their end customers to write reviews about the services that they have utilized. Such reviews provide vital sources of information on these products or services. This information is utilized by the future potential customers before deciding on purchase of new product...
Article
This paper addresses problem of predicting direction of movement of stock and stock price index for Indian stock markets. The study compares four prediction models, Artificial Neural Network (ANN), Support Vector Machine (SVM), random forest and naive-Bayes with two approaches for input to these models. The first approach for input data involves co...
Article
The paper focuses on the task of predicting future values of stock market index. Two indices namely CNX Nifty and S&P Bombay Stock Exchange (BSE) Sensex from Indian stock markets are selected for experimental evaluation. Experiments are based on 10 years of historical data of these two indices. The predictions are made for 1–10, 15 and 30 days in a...
Article
Full-text available
Social bookmarking system is a web-based resource sharing system that allows users to upload, share and organize their resources i.e. bookmarks and publications. The system has shifted the paradigm of bookmarking from an individual activity limited to desktop to a collective activity on the web. It also facilitates user to annotate his resource wit...
Article
Full-text available
Recommender system helps customers buying products/items efficiently and at the same time benefits the business. It can be built using approaches like: (1) Collaborative Filtering (2) Content Based Filtering and (3) Hybrid Filtering. In Collaborative Recommender System, ratings of the most similar users (in case of user based collaborative filterin...

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