Text Sentiment Analysis for Intelligent Transportation Systems by Using Web-Based Traffic Data: A Descriptive Study | Chapter 2 | Recent Advances in Mathematical Research and Computer Science Vol. 10

  In essence, transportation systems serve people, yet modern intelligent transportation systems (ITSs) have failed to consider public opinion. It is required to collect and analyse public wisdom and opinions in order to complete the ITS space. However, only a few research concentrated on the subject of transportation, which failed to meet the severe standards of intelligent transportation systems in terms of safety, efficiency, and information sharing (ITSs). We suggest traffic sentiment analysis (TSA) as a novel approach for addressing this issue, which gives modern ITSs a fresh perspective. This paper proposes TSA methods and models, as well as a comparison of the benefits and drawbacks of rule- and learning-based approaches using online data. We used the rule-based approach to solve real-world challenges, presented an architectural design, built associated bases, illustrated the process, and talked about online data collecting. The "yellow light rule" and China's "fuel price" were used to demonstrate the efficacy of our strategy. Our efforts will contribute to the advancement of TSA and its applications. This research paper proposes a new classification system for future development. To solve this problem, we employ a fuzzy extension known as the Fuzzy Naive Bayes classifier for the opinion mining process, which generalises the meaning of an attribute so that it has a collection of values to a specific degree of truth rather than a single value. This fuzzy naive Bayesian classification uses a hybrid classifier that combines Fuzzy Set Theory with a Naive Bayes classification.

Author(s) Details:

R. Jayavadivel,
Department of Computer Science and Engineering, School of Engineering, Presidency University, Bangalore, Karnataka - 560064, India.


N. Rajkumar,
Department of Computer Science and Engineering, School of Engineering, Presidency University, Bangalore, Karnataka - 560064, India.


B. Prabhu Shankar,
Department of Computer Science and Engineering, School of Engineering, Presidency University, Bangalore, Karnataka - 560064, India.


E. Vetrimani,
Department of Computer Science and Engineering, School of Engineering, Presidency University, Bangalore, Karnataka - 560064, India.


C. Viji,
Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, Karnataka – 560045, India.

G. Aarthy,
Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, Karnataka – 560045, India.

Please see the link here: https://stm.bookpi.org/RAMRCS-V10/article/view/6270

Novel Scheme for Movie Recommendation System Using User Similarity and Opinion Mining: A Recent Study | Chapter 9 | Recent Developments in Engineering Research Vol. 12

 Because of the increased number of users in a mobile environment, movie recommender systems have become an important research topic. This system assists in recommending top-k movies to the target user. To make it easier for consumers to find the best movies, a comprehensive aggregate of user preferences, sentiments (emotions), and reviews is required to recommend movies. When dealing with the recommendation system, however, we must consider timeliness and accuracy. Various recommendation schemes have been presented, including collaborative filtering, a content-based recommender system, and others. as well as a hybrid recommender system In this paper, we present a movie recommendation system based on a new user similarity metric and opinion mining. The primary goal of this work is to identify the different types of movie opinions (positive, negative, or neutral) and to provide users with a top-k list of suggestions. We extract aspect-specific ratings from reviews and recommend reviews to users based on user similarity and rating patterns. Finally, the proposed movie recommendation system was validated using a variety of evaluation criteria, and it outperformed conventional systems.

Author(s) Details

R. Nagamanjula
Mother Teresa Women’s University, Tamilnadu, India.

Dr. A. Pethalakshmi
Govt. Arts College for Women, Nilakkottai, Dindigul District, Tamilnadu, India.

View Book :- https://stm.bookpi.org/RDER-V12/article/view/1486