## Abstract The amount of information on the Web has been expanding at an enormous pace. There are a variety of Web documents in different genres, such as news, reports, reviews. Traditionally, the information displayed on Web sites has been static. Recently, there are many Web sites offering conte
Introduction to the JASIST Special Topic issue on web retrieval and mining: A machine learning perspective
β Scribed by Hsinchun Chen
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 62 KB
- Volume
- 54
- Category
- Article
- ISSN
- 1532-2882
No coin nor oath required. For personal study only.
β¦ Synopsis
Web Retrieval and Mining: Introduction
Research in information retrieval (IR) has advanced significantly in the past few decades. Many tasks, such as indexing and text categorization, can be performed automatically with minimal human effort. Machine learning has played an important role in such automation by learning various patterns such as document topics, text structures, and user interests from examples.
In recent years, it has become increasingly difficult to search for useful information on the World Wide Web because of its large size and unstructured nature. Useful information and resources are often hidden in the Web. While machine learning has been successfully applied to traditional IR systems, it poses some new challenges to apply these algorithms to the Web due to its large size, link structure, diversity in content and languages, and dynamic nature. On the other hand, such characteristics of the Web also provide interesting patterns and knowledge that do not present in traditional information retrieval systems.
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