and decision trees to ascertain the sentiment for a new text document based on patterns from previous training" documents with assigned sentiment scores Section 5.7 Review Questions 1. What are some of the main challenges the Web poses for knowledge discovery? The Web is too big for effective data mining The Web is too complex The Web is too dynamic The Web is not specific to a domain The Web has everything 2. What is Web mining? How does it differ from regular data mining or text mining? Web mining is the discovery and analysis of interesting and useful information from the Web and about the Web, usually through Web-based tools. Text mining is less structured because it's based on words instead of numeric data 3. What are the three main areas of Web mining? The three main areas of Web mining are Web content mining, Web structure mining, and Web usage (or activity) mining 4. What is Web content mining? How can it be used for competitive advantage? Web content mining refers to the extraction of useful information from Web pages. The documents may be extracted in some machine-readable format so that automated techniques can generate some information about the Web pages Collecting and mining Web content can be used for competitive intelligence (collecting intelligence about competitors'products, services, and customers), which can give your organization a competitive advantage 5. What is Web structure mining? How does it differ from Web content mining? Web structure mining is the process of extracting useful information from the links embedded in Web documents. By contrast, Web content mining involves analysis of the specific textual content of web pages. So, Web structure mining is more related to navigation through a website, whereas Web content mining is more related to text mining and the document hierarchy of a particular web page Copyright C2018 Pearson Education, Inc.9 Copyright © 2018Pearson Education, Inc. and decision trees to ascertain the sentiment for a new text document based on patterns from previous “training” documents with assigned sentiment scores. Section 5.7 Review Questions 1. What are some of the main challenges the Web poses for knowledge discovery? • The Web is too big for effective data mining. • The Web is too complex. • The Web is too dynamic. • The Web is not specific to a domain. • The Web has everything. 2. What is Web mining? How does it differ from regular data mining or text mining? Web mining is the discovery and analysis of interesting and useful information from the Web and about the Web, usually through Web-based tools. Text mining is less structured because it’s based on words instead of numeric data. 3. What are the three main areas of Web mining? The three main areas of Web mining are Web content mining, Web structure mining, and Web usage (or activity) mining. 4. What is Web content mining? How can it be used for competitive advantage? Web content mining refers to the extraction of useful information from Web pages. The documents may be extracted in some machine-readable format so that automated techniques can generate some information about the Web pages. Collecting and mining Web content can be used for competitive intelligence (collecting intelligence about competitors’ products, services, and customers), which can give your organization a competitive advantage. 5. What is Web structure mining? How does it differ from Web content mining? Web structure mining is the process of extracting useful information from the links embedded in Web documents. By contrast, Web content mining involves analysis of the specific textual content of web pages. So, Web structure mining is more related to navigation through a website, whereas Web content mining is more related to text mining and the document hierarchy of a particular web page