II FQIQTI: An implementation of the conceptualist approach to Internet Information Retrieval M. Weideman I Cape Peninsula University of Technology, Cape Town, South Africa meliusw@yahoo.com Received: 6 th June 2003 Accepted: 8 th May 2004 The objective of: this research project was to evaluate searching methodologies used by undergraduate learners in searching for academic information, and to design an aid if required. Literature surveys indicated that the sheer size of the Internet and lack of categorization of the information available makes finding relevant information a daunting task. Other problems include a lack of clear search specification formulation and inefficient usage of tim e and computing power by loading and using one search engine at a time. It w as also clear from the literature that Internet searchers have difficulty in general to locate relevant information. The methodology used included empirical experiments involving a total of 1109 learners in a series of empirical experiments to address this situation. Their failure/success, methodology and a number of other factors were measured, and an instrument was designed to overcome these problems. The main conclusion was that the use of this instrument (called FOIOT/:Finder Of Information On The Internet) increased the chances of success under controlled circumstances dramatically. This was achieved by hiding the opera tiona list detail from the user, allowing him/ her to concentrate on conceptualizing the topic. Keywords: Internet searching, Information retrieval, information interface, search engine, FOIOTI. Introduction The Internet offers its users the world's largest and most complex, chaotic and unstructured search space (Sherman 1999: 54). Although programs such as friendly browsers and free search engines exist to assist the user to find his/her way around this unknown data repository, general consensus exists that navigating the Internet is not a straightforward task (Voorbij J 999: 598). One specific skill,which eludes many of these average users, isthe findingof relevant information on the Internet in a short time (Brewer 200 I: 54). An Internet search engine is a program, which allows the user to either specify (a) keyword(s), or drill down into a topic through various levels of directories. Both approaches should lead the user to 'the perfect website', which will contain the exact information required. Commonly used search engines include Google, AIiTheWeb, Yahoo! and MSN Search (Sullivan2003). These search engines each contain a front end, an index and a set of collectors. The front end is the human interface, Le.,what the user interacts with on the screen during the searching process. The index is a large file which contains detail about millions of websites, and it is this file (not the Internet itself) which is queried when a user searches for information via a search engine. The collectors are either human editors (as with Yahoo) or automated programs called spiders, bots or crawlers (as used by Google and AltaVista). Both types of collectors gather information about available websites, and build it into the index file (Sullivan 1999: 34, Sullivan2002). All search engines offer a number of features to enable the user to find information with ease. However, it has been proven that most users do not availthemselves of these features (Weideman 200 I: 197).The purpose of this article is to introduce the reader to an alternative approach to Internet searching - one that does not presuppose any knowledge of search engines or their syntax and operators. This approach is aimed at the typical IS/IT (Information Systems / Information Technology) university or technikon student who is not familiarwith the detailed syntax of search engines. The most basic form of Internet searching (inherited from pre-Internet systems) is to load a search engine, type in a single word, and instruct the search engine to find the information. Not surprisingly, this method seldom delivers relevant answers, especially if the word has many different interpretations (Siegfried et 0/. 1993: 273). As an example, common words like 'religion,' 'computers,' 'sport' and 'weather' produced the following approximate numbers of answers in four separate searches on Google: 12 000 000, 20 200 000, 23 100 000 and 28 000 000. A logical next step would be to use either a very specific single word, or more than one word as a search query. Multiple-word queries fall into one of a number of categories: phrase searching, Boolean operators, inclusion/exclusion, combinational operators, and other methods. I. Prof. Melius Weideman is Head: Research Planning and Capacity Building, Cape Peninsula University of Technology, Cape Town, South Africa. SA Jnl Libs & Info Sci 2005 71(I)