The evolution of the World Wide Web and Search engines has brought the abundant and ever growing pile of data and information on our finger tips. It has now become a popular and important resource for doing information research and analysis.
Today, Web research services are becoming more and more complicated. It involves various factors such as business intelligence and web interaction to deliver desired results.
Web Researchers can retrieve web data using search engines (keyword queries) or browsing specific web resources. However, these methods are not effective. Keyword search gives a large chunk of irrelevant data. Since each webpage contains several outbound links it is difficult to extract data by browsing too.
Web mining is classified into web content mining, web usage mining and web structure mining. Content mining focuses on the search and retrieval of information from web. Usage mining extract and analyzes user behavior. Structure mining deals with the structure of hyperlinks.
Web mining services can be divided into three subtasks:
Information Retrieval (IR): The purpose of this subtask is to automatically find all relevant information and filter out irrelevant ones. It uses various Search engines such as Google, Yahoo, MSN, etc and other resources to find the required information.
Generalization: The goal of this subtask is to explore users' interest using data extraction methods such as clustering and association rules. Since web data are dynamic and inaccurate, it is difficult to apply traditional data mining techniques directly on the raw data.
Data Validation (DV): It tries to uncover knowledge from the data provided by former tasks. Researcher can test various models, simulate them and finally validate given web information for consistency.
Source: http://ezinearticles.com/?Basics-of-Online-Web-Research,-Web-Mining-and-Data-Extraction-Services&id=4511101
Today, Web research services are becoming more and more complicated. It involves various factors such as business intelligence and web interaction to deliver desired results.
Web Researchers can retrieve web data using search engines (keyword queries) or browsing specific web resources. However, these methods are not effective. Keyword search gives a large chunk of irrelevant data. Since each webpage contains several outbound links it is difficult to extract data by browsing too.
Web mining is classified into web content mining, web usage mining and web structure mining. Content mining focuses on the search and retrieval of information from web. Usage mining extract and analyzes user behavior. Structure mining deals with the structure of hyperlinks.
Web mining services can be divided into three subtasks:
Information Retrieval (IR): The purpose of this subtask is to automatically find all relevant information and filter out irrelevant ones. It uses various Search engines such as Google, Yahoo, MSN, etc and other resources to find the required information.
Generalization: The goal of this subtask is to explore users' interest using data extraction methods such as clustering and association rules. Since web data are dynamic and inaccurate, it is difficult to apply traditional data mining techniques directly on the raw data.
Data Validation (DV): It tries to uncover knowledge from the data provided by former tasks. Researcher can test various models, simulate them and finally validate given web information for consistency.
Source: http://ezinearticles.com/?Basics-of-Online-Web-Research,-Web-Mining-and-Data-Extraction-Services&id=4511101
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