Intelligent Web Mining: Using Text, Image, Audio, and Video Data to Gain Knowledge
T. Yogesha, Dr.S.N. Thimmaraju · Journal of Internet Services and Information Security · 2025
There are various techniques for extracting relevant conclusions from various types of data the efficient approach that combines the power of data analysis, with intelligence and machine learning is smart web mining which enables the extraction of diverse data forms including text documents, videos and audio files and images effectively and efficiently. This study delves into the techniques and resources employed in web mining to accurately assess and comprehend data. Most web data is in the form of text. They are commonly fetched with algorithms like topic modelling, sentiment analysis, and other machine learning approaches known as natural language processing (NLP). These sources can appear to be inactive and unstructured, but indeed, these methods and other computer language model frameworks can decipher important information from them. For image data, algorithms for object detection use computer vision methods such as convolutional neural networks (CNN). While trying to detect patterns and information, faces or objects are identified and classified. Emotion, speaker identification, and automatic speech recognition are some of the applications of mining audio with neural networks, spectral, and speech to text analysis. The analysis of motion and interaction of objects in films is done using a fusion of visual and auditory analysis with guided methods. In building such frameworks, various algorithms giving the ability to process data from different sources are integrated. In handling the huge and heterogeneous information on the internet, intelligent web mining systems use the combination of the cloud computing service and computers that were built on the decentralized databases. Over and above sophisticated machine learning algorithms are trained with the datasets when the need for accuracy and flexibility is considered as the unsupervised learning technique reveals the hidden associations or patterns. This study highlights smart web mining's potential as a transformative tool for extracting insights from various data types, paving the way for innovative applications in a data-driven world.