In an era of unprecedented data growth, web mining has become essential for uncovering actionable insights from the vast expanse of online information. This study provides a comprehensive overview of web mining, focusing on extracting valuable insights such as user behavior patterns, trend identification, and novel information discovery. It categorizes web mining into three pivotal areas: web content mining, web structure mining, and web usage mining, and highlights key techniques, tools, and algorithms associated with each. The paper addresses critical challenges including data privacy, algorithmic bias, and the management of unstructured data, while also examining ethical considerations like user consent and data security. The unique contributions of this study lie in its detailed comparison of existing methodologies and the introduction of a new framework designed to tackle ethical concerns. Aimed at both researchers and practitioners, this paper offers actionable insights to advance the field of web mining, underscoring its interdisciplinary applications and the imperative of ethical vigilance.
Key words: Web mining, web mining categories, web mining techniques, web mining tools, web mining algorithms, web mining ethical implications.
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