1 / 67

WEB MINING

WEB MINING. Dr. GOPINATH GANAPATHY BHARATHIDASAN UNIVERSITY. Data Mining vs. Web Mining. Traditional data mining data is structured and relational well-defined tables, columns, rows, keys, and constraints. Web data Semi-structured and unstructured readily available data

peavler
Download Presentation

WEB MINING

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. WEB MINING Dr. GOPINATH GANAPATHY BHARATHIDASAN UNIVERSITY

  2. Data Mining vs. Web Mining • Traditional data mining • data is structured and relational • well-defined tables, columns, rows, keys, and constraints. • Web data • Semi-structured and unstructured • readily available data • rich in features and patterns

  3. Web Mining • The term created by Orem Etzioni (1996) • Application of data mining techniques to automatically discover and extract information from Web data

  4. Web Mining • Web is the single largest data source in the world • Due to heterogeneity and lack of structure of web data, mining is a challenging task • Multidisciplinary field: • data mining, machine learning, natural language • processing, statistics, databases, information • retrieval, multimedia, etc.

  5. Mining the World-Wide Web • The WWW is huge, widely distributed, global information service center for • Information services: news, advertisements, consumer information, financial management, education, government, e-commerce, etc. • Hyper-link information • Access and usage information • WWW provides rich sources for data mining

  6. Web Mining: A more challenging task • Searches for • Web access patterns • Web structures • Regularity and dynamics of Web contents • Problems • The “abundance” problem • Limited coverage of the Web: hidden Web sources, majority of data in DBMS • Limited query interface based on keyword-oriented search • Limited customization to individual users

More Related