International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 11 | Nov 2025
p-ISSN: 2395-0072
www.irjet.net
Web Mining Techniques on Artificial Intelligence Dr.C.Sangeetha1, Mr.N.Krishnan2, Mrs.P.R.Saranya3 1Assissant Professor, Department of Computer Science, Rathinam College of Liberal Arts & Science @ Tips Global
Kovilpalayam, Coimbatore,Tamilnadu, India
2Assissant Professor, Department of Computer Science, Rathinam College of Liberal Arts & Science @ Tips Global
Kovilpalayam, Coimbatore,Tamilnadu, India
3Assissant Professor, Department of Computer Science, Rathinam College of Liberal Arts & Science @ Tips Global
Kovilpalayam, Coimbatore,Tamilnadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------categorization. The way that computers are programmed to Abstract— Web mining relies heavily on artificial
process natural languages is through their interactions with human language. Natural language processing uses machine learning, a dependable technology, to extract meaning from human languages. In NLP, a machine records the audio of a human conversation. The audio-to-text exchange follows, and after that, the text is processed to turn the data into audio. The machine then reacts to people using the audio. Natural language processing is used in word processors like Microsoft Word to check text for grammar errors, IVR (Interactive Voice Response) programs used in contact centers, and language translation programs like Google Translate.
intelligence (AI), which makes it possible to analyze enormous volumes of unstructured data and identify important patterns and insights. Tasks like content recommendation, user analysis, and web page classification are automated with Artificial Intelligence techniques like machine learning and natural language processing. This allows businesses to personalize user experiences, improve website design, and identify potential customers.
Keywords— Classification, Machine Learning, Natural Language Processing, content recommendation.
I. Introduction
C. Image and Video Analysis
Web mining has been greatly impacted by artificial intelligence (AI), which offers more effective and potent methods for knowledge extraction, analysis, and application from the massive and ever-changing amount of information available on the World Wide Web..
Web images and videos are analyzed by AI algorithms, particularly deep learning models like convolution neural networks, for content analysis, object detection, and facial recognition. D. Recommender Systems
II. Artificial Intelligence Techniques in Web Mining
In order to provide relevant material, goods, or services, AI examines a user's tastes, past actions, and an item's attributes.
A. Machine Learning (ML) Patterns in web data, including user browsing patterns, click stream data, and search queries, are found using A branch of machine learning called "deep learning" uses artificial neural networks to analyze data in order to make predictions. Supervised learning, unsupervised learning, and other machine learning algorithms are among the many reinforcement learning. The algorithm in unsupervised learning doesn't act on classified data without any direction. The training data, which is a collection of an input item and the intended output, is used in supervised learning to infer a function. Machines utilize reinforcement learning to determine the best option that should be considered and to take appropriate actions to increase the reward.
III. APPLICATIONS OF Artificial Intelligence in Web Mining A. Personalization Algorithms powered by artificial intelligence sift through user data in order to personalize website content, offers, recommendations, and suggestions to each individual. B. Web Usage Mining Understanding how people engage with a website, finding popular pages, and improving navigation are all goals of user behavior analysis.
B. Natural Language Processing (NLP)
C. Content Recommendation
Web pages text content can be analyzed using natural language processing (NLP) techniques to extract important information and determine subjects and sentiment. This is very helpful for tasks like sentiment analysis and content
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