A Fuzzy Semantic Information Retrieval System for Transactional Applications

Abstract

In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is encouraging. Similarly, the smaller amount of more precise information retrieved by the system will positively impact the response time perceived by the users.Keywords: Fuzzy set, Query, Information, Fuzzy Inference Engine, Response time INTRODUCTIONInformation Retrieval (IR) is the science of searching for information in documents, searching for metadata which describe documents, or searching within databases, whether relational stand-alone databases or a hypertextually-networked database such as the World Wide Web. The core functionality of an IR system is the retrieval of data from a database whose abstraction matches the description of an ideal object, inferred from a query (Bellman et al., 1992). A complex algorithm is used to search through the information, retrieve, and deliver the results to the user.Traditional information retrieval models as employed in current search engines typically express a query as a set of keywords in which Boolean expressions involving words are used as terms to find information (Huang & Tsai, 2005). These keyword indexing systems and Boolean logic queries are sometimes equipped with statistical methods (Buckley & Fuhr, 1990), for instance, using frequency of occurrence of a keyword to strengthen the relationship between keyword and object. This model, called the keyword-based information retrieval model, uses keyword lists to describe the contents of information objects. The keyword list is a description that does not say anything about semantic relationships between keywords. According to Baeza-Yates and Ribiero (1999) the simplicity of these models usually prevents the formulation of more elaborate querying tasks. In addition, they give unsatisfactory query results when the semantic content of the query forms can not be easily represented.In this study, a fuzzy semantic information retrieval model is developed for query tasks that can not be translated into clear forms. For instance, a potential buyer may be interested in an elementary Java textbook that introduces graphics programming with a pinch of data structure together with a bit of design patterns. Formulating a query using conventional retrieval models to describe the buyer's information needs specified above is difficult due to the ambiguity introduced in the specification of intensity of the data structure content and the concentration of design patterns to be included in said textbook. In a related manner, the use of advanced features of a typical search engine by users has always been limited because most users do not kn...