In this fifth installment of our artificial intelligence research series, we explore projects 61 through 70. These initiatives highlight how machine learning and data mining are being used to refine consumer experiences, enhance accessibility for the differently-abled, and provide critical diagnostic support in healthcare and education.
I. Retail Intelligence and Consumer Protection
61. A Commodity Search System For Online Shopping Using Web Mining
As e-commerce platforms proliferate, consumers often struggle to find the best prices due to fragmented data. This system utilizes web mining techniques to proactively track consumer demand. When a commodity's price falls below a user's specified threshold on any monitored website, the system notifies the consumer and provides historical price data to aid in the purchasing decision.
62. Fake Product Review Monitoring & Removal for Genuine Ratings (PHP)
To combat the issue of "false positive" reviews—often posted by companies to artificially boost their own products—this system identifies fake comments using opinion mining. By tracking user IP addresses and analyzing review posting patterns, the system flags suspicious activity and enables administrators to remove fraudulent content, ensuring users see only genuine feedback.
63. Product Review Analysis for Genuine Rating
This advanced analysis platform allows registered users to rate multiple products and uses sentiment-based keywords to categorize feedback as good, bad, or worst. By applying specific weightage to positive and negative keywords in a database, the system generates an appropriate rank for each product, helping prospective buyers make informed choices based on aggregated user sentiment.
II. Predictive Analytics in Media and Transportation
64. Movie Success Prediction Using Data Mining (PHP)
This project employs a mathematical model to forecast whether a film will be a "flop," "hit," or "super hit" before its release. By weighing historical data for actors, directors, writers, and music directors—and factoring in marketing budgets and release dates—the system provides a success probability that helps both distributors and viewers.
65. Traffic Sign Recognition System using CNN
A vital component for the development of autonomous vehicles and driver assistance, this system uses a Deep Convolutional Neural Network (CNN) to detect road signs from images, videos, or real-time camera feeds. It provides the name of the recognized sign along with a probability score for accuracy, potentially reducing accidents by keeping drivers informed of signs they might overlook.
III. Specialized Healthcare Diagnostics and Accessibility
66. Parkinson’s Detector System using Python
Early identification of Parkinson’s disease is challenging for non-specialists, yet critical for managing symptoms that worsen over time. This predictive analytics framework uses a CNN model and the XGBoost algorithm to analyze images of user-uploaded spiral and wave drawings. The system can detect the user’s health status in seconds, facilitating earlier clinical intervention.
67. Depression Detection System using Python
This platform facilitates mental health self-evaluation by correlating linguistic characteristics and facial expressions with likely depression symptoms. Utilizing Naive Bayes for diagnostic quizzes and CNN for facial emotion detection during a one-minute recording, the system identifies specific types of depression (anxiety, PTSD, or bipolar) and recommends nearby clinics for consultation.
68. Sign Language Recognition Using Python
To bridge the communication gap for the hearing and speech impaired, this system provides a computer-based method for interpreting hand gestures. Using a CNN model, the platform detects hand signs through a real-time camera feed and translates them into numbers or alphabets, allowing others to understand what the differently-abled individual is communicating.
IV. Educational Support and Career Intelligence
69. College Enquiry Chat Bot
This web application simplifies the administrative burden of student inquiries by using artificial intelligence algorithms to understand and answer queries related to college activities. Students can chat in any format to receive information about admission dates, sports days, or cultural events, saving time for both students and staff by eliminating the need for in-person office visits.
70. Stream Analysis For Career Choice Aptitude Tests
Designed to help students make unbiased career choices, this system automates IQ and aptitude testing. It matches user responses against pre-defined database answers and features an "expert mode" that adjusts difficulty based on performance. The system provides instant, accurate results in an excel report, effectively reducing the manual workload of examiners while providing a clear career direction for the user.
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…till the next post, bye-bye & take care
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