ABSTRACT
Despite the usefulness of database technologies, users of online information retrieval systems are often overwhelmed by the amount of current information, the subject and system knowledge required to access this information, and the constant influx of new information [7]. The result is termed information overload [3]. A second difficulty associated with information retrieval and information sharing is the classical vocabulary problem, which is a consequence of diversity of expertise and backgrounds of system users [6, 21, 22]. Previous research in information science and in human-computer interactions has shown that people tend to use different terms (vocabularies) to describe a similar concept—the chance of two people using the same term to describe an object or concept is less than 20% [22], The “fluidity” of concepts and vocabularies, especially in the scientific and engineering domains, further complicates the retrieval issue [6, 14, 20]. A scientific or engineering concept may be perceived differently by different researchers and it may also convey different meanings at different times. To address the information overload and the vocabulary problem in a large information space that is used by searchers of varying backgrounds a more proactive search aid is needed.
