Sentiment analysis of English Text using Raspberry Pi
Tiwari, Raj Kumar (2020)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2020052313154
https://urn.fi/URN:NBN:fi:amk-2020052313154
Tiivistelmä
IoT devices have been used in most of the areas in daily life these days. IoT devices are the same devices used for single or multipurpose works in the home, offices, factories, industries, machinery. The data collected from the operations of such devices are usually collected and analyzed to generate further productivity and aid. Previously, the data were analyzed by humans and calculators. Nowadays, the evolving technology and programs help to understand data patterns and generate new algorithms which in turn provide more sophisticated assistance with a more advanced approach.
An example of product development and its process is explained in this thesis to understand the basic structure of IoT devices using natural language text processing to create a basic understanding of the topic. For this purpose, an embedded device was developed including a branch of machine learning to recognize the sentiment of English Text.
The thesis aims to give a conceptual overview and explain the process itself. The analysis of free text information comments and feedback helps to improve services and understand people’s attitude towards the service with the help of a small processing unit such as Raspberry Pi. The device use case is aimed at customer-oriented services and it aims to collect the necessary feedback and analyze it. The device created is a basic structure that can be further modified and developed using models such as face recognition. The thesis explains the whole process of development and presents the result.
An example of product development and its process is explained in this thesis to understand the basic structure of IoT devices using natural language text processing to create a basic understanding of the topic. For this purpose, an embedded device was developed including a branch of machine learning to recognize the sentiment of English Text.
The thesis aims to give a conceptual overview and explain the process itself. The analysis of free text information comments and feedback helps to improve services and understand people’s attitude towards the service with the help of a small processing unit such as Raspberry Pi. The device use case is aimed at customer-oriented services and it aims to collect the necessary feedback and analyze it. The device created is a basic structure that can be further modified and developed using models such as face recognition. The thesis explains the whole process of development and presents the result.