Information retrieval has evolved from searches of references, to abstracts, to documents. Search on the Web involves search engines that promise to parse full-text and other files: audio, video, and multimedia. With the indexable Web at 320 million pages and growing, difficulties with locating relevant information have become apparent. The most prevalent means for information retrieval relies on syntax-based methods: keywords or strings of characters are presented to a search engine, and it returns all the matches in the available documents. This method is satisfactory and easy to implement, but it has some inherent limitations that make it unsuitable for many tasks. Instead of looking for syntactical patterns, the user often is interested in keyword meaning or the location of a particular word in a title or header. This paper describes some precise search approaches in the environmental domain that locate information according to syntactic criteria, augmented by the utilization of information in a certain context. The main emphasis of this paper lies in the treatment of structured knowledge, where essential aspects about the topic of interest are encoded not only by the individual items, but also by their relationships among each other. Examples for such structured knowledge are hypertext documents, diagrams, logical and chemical formulae. Benefits of this approach are enhanced precision and approximate search in an already focused, context-specific search engine for the environment: EnviroDaemon.


Computer Sciences



URL: https://digitalcommons.calpoly.edu/csse_fac/9