QUESTIOZ
  • Home
  • Archives
  • Guidelines
  • Team
  • Contact
  • Research Essays
  • Research Papers

Sentiment Analysis on Machine LearningBased on HP Taccola Printer Customer Sentiment Data

10/29/2021

0 Comments

 
Author : Spencer Chang 
Mountain View High School, Vancouver, Washington, USA 


Abstract
​The Trillium printer coming out for the next generation of HP printers comes from the design of the Taccola printer, which had notably bad reviews. In order to make a better printer, HP wanted to capitalize on the weak points of the Taccola printer, keep the strong points, and design Trillium with the best of both worlds. 17000 customer comments from the last 3 months were analyzed to find general sentiment on the product. Using Python machine learning, the comments were run though sentiment models in order to deliver a minimum of 80% of sentiments correct. Using Sentence-Bert, SentenceTransformer, and spatial distance, a 90% accuracy rate was achieved. In conclusion, the main weakness of the Taccola needs to change its app in order to function smoother.




Sentiment Analysis on Machine Learning Based on HP Taccola Printer Customer Sentiment Data
File Size: 592 kb
File Type: pdf
Download File

0 Comments



Leave a Reply.

    October 2021 Issue



    Categories

    All


    Archives

    November 2021
    October 2021

    RSS Feed

QUESTION. QUIP. QUESTIOZ.
​

TERMS AND CONDITIONS

STAY IN THE KNOW

Questioz cannot be held responsible for any violation of academic integrity. The intellectual property of all contributing researchers will be respected and protected. Questioz reserves the non-exclusive right to republish submitted material with attribution to the author in any other format, including all print, electronic and online media. However, all individual contributors to Questioz retain the right to submit their work for non-exclusive publication elsewhere.
High School Research Journal Questioz Logo
  • Home
  • Archives
  • Guidelines
  • Team
  • Contact
  • Research Essays
  • Research Papers