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Spatial data mining-Multimedia data mining-Text mining-Mining the world wide web
- 1. SPATIAL DATA MINING-MULTIMEDIADATA MNING-TEXT MINING-MINING THE WORLD WIDE WEB Presented by P. Yuvasri I-MSc(Computer Science) Nadar Saraswathi College Of Arts And Science Theni
- 2. Spatial datamining is the process of uncovering hidden, meaningful patterns and knowledge from large datasets that include geographic or locational information, such as maps, satellite imagery, and GPS coordinates. It differs from traditional data mining by analyzing spatial relationships, autocorrelation, and other unique properties of spatial data, and is used in fields like urban planning, public health, and environmental management to understand phenomena like crime hotspots, land use changes, and disease spread. Key techniques include spatial clustering, classification, trend analysis, and co-location pattern discovery. SPATIAL DATA MINING
- 3. Spatial data miningprovides valuable insights for numerous. Urban Planning Public Health Environmental Management Crime Analysis Geomarketing Spatial data
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- 5. Multimedia datamining is the process of analyzing and extracting meaningful patterns and knowledge from large multimedia databases containing various data types like text, images, audio, and video. It involves applying data mining techniques such as classification, clustering, association, and similarity search to these unstructured or semi-structured datasets to uncover hidden information. This field is applied in areas like digital libraries, content- based retrieval, and the analysis of web data to understand complex information and manage vast multimedia collections. MULTIMEDIA DATA MINING
- 6. Multimedia data isbroadly categorized into two types: Static Media: Data that does not change over time, such as text, images, and graphics. Digital Libraries: Managing and retrieving information from large collections of digital text, images, and videos. Content-Based Retrieval: Finding specific multimedia content based on its visual or audio features rather than just keywords. TYPES OF MULTIMEDIA
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- 8. Text miningis the process of using computers to analyze large volumes of unstructured text data, transforming it into a structured format to discover hidden patterns, topics, keywords, and insights that would be difficult to find manually. It leverages Natural Language Processing (NLP), artificial intelligence (AI), and machine learning to extract knowledge from sources like social media, emails, and articles, enabling businesses to make informed decisions and gain a competitive edge. TEXT MINING
- 9. Text mining involvesseveral steps 1. Data Collection: Gathering text data from diverse sources such as websites, social media platforms, customer reviews, and internal documents. 2. Preprocessing: Cleaning and preparing the text data by removing noise TEXT MINING STEPS
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- 12. "Mining theworld wide web," or Web mining, is the process of applying data mining techniques to extract valuable information and patterns from the vast amount of data available on the World Wide Web. It encompasses three primary categories: web content mining (from page contents), web structure mining (from hyperlink structures), and web usage mining (from user interactions). The goal is to discover patterns that can improve web content, user experience, and inform business strategies. MINING THE WORLD WIDE WEB
- 13. 1. Web ContentMining: This type focuses on extracting useful information and knowledge from the actual content of web pages, such as text, images, and audio. 2. Web Structure Mining: This involves analyzing the hyperlink structure of websites to understand relationships between web pages and how information is organized. Algorithms like PageRank and HITS are used in this process. 3. Web Usage Mining: This category focuses on discovering patterns from user interactions and behavior recorded in web server logs. Analyzing these logs helps understand user navigation patterns, preferences, and overall site usage. Applying Data Mining to the Web
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