Our project revolves around the development of an IOT enabled movie automation environment powered by a perfect IOT device comprising Beacon, NFC technology and Arduino capable of automation and authentication of reviews with real time updates powered with powerful review analysis.
Backed by Sentiment analysis of customer reviews mainly unstructured text, voice and numerical text generated for the movies and theater at the venue and over social media.
Our project constitutes an intricate movie genre recommender engine powered by K-means clustering and Pearson correlation similarity measure.
NFC- Near Field Communication
MovieLens data sets were collected by the GroupLens Research Project at the University of Minnesota. This data set consists of:
100,000 ratings (1-5) from 943 users on 1682 movies.
Each user has rated at least 20 movies
Simple demographic info for the users (age, gender, occupation, zip)
Arduino is a software company, project, and user community that designs and manufactures computer hardware, open, and microcontroller-based kits for building digital devices and interactive objects that can sense and control physical devices.
The project is based on micro controller board designs, produced by several vendors, using various microcontrollers.
These systems provide sets of digital and analog I/O pins that can interface to various expansion boards (termed shields) and other circuits.
The boards feature serial communication interfaces, including Universal Serial Bus (USB) on some models, for loading programs from personal computers.
NFC - Near Field Communication
Near field communication (NFC) is a set of communication protocols that enable two electronic devices, one of which is usually a portable device such as a smartphone, to establish communication by bringing them within 4 cm (2 in) of each other.
NFC tags are passive data stores which can be read, and under some circumstances written to, by an NFC device.
NFC-enabled portable devices can be provided with apps, for example to read electronic tags or make payments when connected to an NFC-compliant apparatus.
NFC tags can be custom-encoded by their manufacturers or use the industry specifications
Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
Introduction to K Means and Pearson Correlation
k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.
The algorithm eventually converges to a point. The algorithm stops when the assignments do not change from one iteration to the next.
In statistics, the Pearson product-moment correlation coefficient (sometimes referred to as the PPMCC or PCC or Pearson's r) is a measure of the linear correlation between two variables X and Y, giving a value between +1 and −1 inclusive, where 1 is total positive correlation, 0 is no correlation, and −1 is total negative correlation. It is widely used in the sciences as a measure of the degree of linear dependence between two variables.
Product Feature - I
Product Feature - II
Register + Rate
Real Time Analysis
Screenshots - II
World Heat Map
Word Frequency Map
Classification by emotion
Classification by Polarity
Screenshot - IV
Screenshot - V
Real time graph update with sentiment calculation from voice
Implementation of an automated management system to provide genuine hassle free reviews and recommendations.
Resolves the lack of real time authentic movie reviews and quick tips around the world
Provides meaningful recommendations based on movie genres and ratings.
Calculation of sentiment of reviews from text, voice and numerical input of customer and over social media.
The analysis solves the dual purpose of judging the social media popularity of the movie as well as performance and quality of service provided to the customer.