Conventional Search Engines Research Articles

Visual representation of document-oriented information on the web

Ever increasing volumes of data motivate us to find new processing and storage methods for provide quick retrieval of information. Users of conventional text-based search engines have faced the problem of digging through thousands of hits returned from keyword searches. There are alternative ways of storing and searching document-related data; these techniques support more direct and simplified document searches guiding the user towards fewer but higher quality selections.One such method is known as WebSOM, Web Self-Organizing Maps, which are based on Kohonen's neural network approach and modern graphical user interfaces. We will show, through the use of APL with this and other methods of information analysis, how to visualize this type of search.

Radiological information searching on the Internet: data banks, search machines and intelligent agents

The Internet plays an important role in a growing number of medical applications. Finding relevant information is not always easy as the amount of available information on the Web is rising quickly. Even the best search engines can only collect links to a fraction of all existing Web pages. In addition, many of these indexed documents have been changed or deleted. The vast majority of information on the Web is not searchable with conventional methods. New search strategies, technologies and standards are combined in intelligent search agents (ISA) and robots, which can retrieve desired information in a specific approach. The article describes differences between ISAs and conventional search engines and how communication between agents improves their ability to find information. Examples of existing ISAs are given and the possible influences on the current and future work in radiology is discussed.