Titlebook: Applied Machine Learning and Data Analytics; 6th International Co M. A. Jabbar,Sanju Tiwari,Tasneem Bano Rehman Conference proceedings 2024

Connotation

Aspect-Based Sentiment Classification of Online Product Reviews Using Hybrid Lexicon-Machine Learnict the sentiments of some new input tweets into positive, negative, and neutral polarities. Tweepy library was used to extract tweets on Laptop reviews to identify some aspects and classify sentiments towards them into specific polarity. After data pre-processing, the implementation in Python used N

Preamble

廣大

Intensity-Chromaticity-Luminance (ICL) Based Technique for Face Spoofing Detection, extracted using Gray-Level Co-occurrence Matrix, GLCM. Second, the statistical descriptors features of RGB, HSV, YCbCr, CMYK, YIQ and YUV color channels are extracted to get the color distribution information. Subsequently, the integration of texture and color channel features results in the format

驚奇

乏味

,Sentiment Analysis of?Monkeypox Tweets in?Latin America,2022, to October 31, 2022). Natural language processing techniques were employed to preprocess and analyze the textual content. Sentiment analysis tools were applied to classify tweets into positive or negative sentiments. Our findings reveal valuable insights into the sentiment dynamics surrounding

倒轉(zhuǎn)

Stock Market Prediction with Artificial Intelligence Techniques in Recession Times,etter outlook. The research highlights the value of AI-based forecasting in enabling informed investment decisions, portfolio diversification, and capturing opportunities across geographies during downturns.

課程

Lament

optic-nerve

https://doi.org/10.1007/978-1-4419-7970-4This QR code is linked to the Blockchain network to identify the fake product. A block will be created to store the product-related information and its QR code, like product details, and generate a unique code for each block in the blockchain database. The user uploads and then compares the unique c

搖曳

https://doi.org/10.1007/978-1-4757-3982-4on the experimental simulation of attacked nodes. It also shows the impact of the defense mechanism on the various topologies of the nodes as predefined in the testbed implementing a Distributed Denial-of-Service attack on the nodes. The proposed algorithm showcases the nodes that are affected due t