Boolean Information Retrieval System Research Articles

An Algorithm for Semantic Expansion of Queries in a Boolean Information Retrieval System

An Algorithm for Semantic Expansion of Queries in a Boolean Information Retrieval System

Boolean search: Current state and perspectives

Most of the operational information retrieval (IR) systems in existence today use Boolean logic during search. Such systems are usually called Boolean IR systems. These systems, as any other IR systems, are not perfect and the problem of their development (and hence providing better quality service for real users) is one of the most important problems in Information Science. From this viewpoint, the article analyzes existing criticisms of operational systems and points out some of their positive features. At the same time, certain negative effects which hinder the development of existing systems are considered. Finally, the article provides several conclusions about using Boolean logic in developing multiversion IR systems.

The use of genetic programming to build Boolean queries for text retrieval through relevance feedback

We report here on preliminary work on the use of evolutionary computing techniques which aims to improve Boolean information retrieval system performance through relevance feedback. There are many evolutionary techniques in computing, such as neural networks and genetic algorithms. One specific form of genetic algorithm technique has been used in our study: that of genetic programming. Terms from relevant documents are used to randomly create Boolean queries. Boolean queries are thought of as genetic programming organisms and, as such, are used for breeding to produce new organisms. Organisms which perform well, in terms of how good they are at retrieval, are given a better chance of being selected for breeding, with the result being that the overall fitness of the organisms improve to some extent. The aim is to develop the best Boolean query for an information need, given a small corpus of test documents, and then to use that query on the full collection to retrieve yet more relevant documents.

An extended fuzzy linguistic approach to generalize boolean information retrieval

The generalization of Boolean information retrieval systems is still of interest to scholars. In spite of the fact that commercial systems use Boolean retrieval mechanisms, such systems still have some limitations. One of the main problems is that such systems lack the ability to deal well with imprecision and subjectivity. Previous efforts have led to the introduction of numeric weights to improve both document representations (term weights) and query languages (query weights). However, the use of weights requires a clear knowledge of the semantics of the query in order to translate a fuzzy concept into a precise numeric value. Moreover, it is difficult to model the matching of queries to documents in a way that will preserve the semantics of user queries. A linguistic extension has been generated, starting from an existing Boolean weighted retrieval model and formalized within fuzzy set theory, in which numeric query weights are replaced by linguistic descriptors that specify the degree of importance of the terms. In the past, query weights were seen as measures of the importance of a specific term in representing the query or as a threshold to aid in matching a specific document to the query. The linguistic extension was originally modeled to view the query weights as a description of the ideal document, so that deviations would be rejected whether a given document had term weights that were too high or too low. This paper looks at an extension to the linguistic model that is not symmetric in that documents with a term weight below the query weight are treated differently than documents with a term weight above the query weight.

A fuzzy linguistic approach generalizing Boolean Information Retrieval: A model and its evaluation

The generalization of Boolean Information Retrieval Systems (IRS) is still an open research field; in fact, though such systems are diffused on the market, they present some limitations; one of the main features lacking in these systems is the ability to deal with the “imprecision” and “subjectivity” characterizing retrieval activity. However, the replacement of such systems would be much more costly than their evolution through the incorporation of new features to enhance their efficiency and effectiveness. Previous efforts in this area have led to the introduction of numeric weights to improve both document representation and query language. By attaching a numeric weight to a term in a query, a user can provide a quantitative description of the “importance” of that term in the documents he or she is looking for. However, the use of weights requires a clear knowledge of their semantics for translating a fuzzy concept into a precise numeric value. Our acquaintance with these problems led us to define, starting from an existing weighted Boolean retrieval model, a linguistic extension, formalized within fuzzy set theory, in which numeric query weights are replaced by linguistic descriptors which specify the degree of importance of the terms. This fuzzy linguistic model is defined and an evaluation is made of its implementation on a Boolean IRS. © 1993 John Wiley & Sons, Inc.

Extended Boolean information retrieval

In conventional information retrieval Boolean combinations of index terms are used to formulate the users'' information requests. While any document is in principle retrievable by a Boolean query, the amount of output obtainable by Boolean processing is difficult to control, and the retrieved items are not ranked in any presumed order of importance to the user population. In the vector processing model of retrieval, the retrieved items are easily ranked in decreasing order of the query-record similarity, but the queries themselves are unstructured and expressed as simple sets of weighted index terms. A new, extended Boolean information retrieval system is introduced which is intermediate between the Boolean system of query processing and the vector processing model. The query structure inherent in the Boolean system is preserved, while at the same time weighted terms may be incorporated into both queries and stored documents; the retrieved output can also be ranked in strict similarity order with the user queries. A conventional retrieval system can be modified to make use of the extended system. Laboratory tests indicate that the extended system produces better retrieval output than either the Boolean or the vector processing systems.

Information Retrieval Systems an Algebraic Approach II

This paper is the second of the three parts of the work on the information retrieval systems proposed by Salton (see [13]). The system is defined by the notions of a partially ordered set of requests (A, ⩽), the set of documents X and a monotonic retrieval function U : A → 2X. Different conditions imposed on the set A and a function U make it possible to obtain various classes of information retrieval systems. We investigate systems in which (A, ⩽) is a partially ordered set, a lattice, a pseudo-Boolean algebra and a Boolean algebra. In my paper these systems are called partially ordered information retrieval systems (po-systems), lattice information retrieval systems (l-systems), pseudo-Boolean information retrieval systems (pB-systems) and Boolean information retrieval systems (B-systems). The first part concerned po-systems and l-systems. The second part deals with pB-systems and B-systems. In the third part systems with a partial access are investigated. The present part discusses the pB-systems and B-systems. The problems connected with the properties of sets of attributes are investigated. The method of constructing a selective system for a pB-system and a B-system is given. The problem related to the minimalization of systems are investigated.

Information Retrieval Systems, an Algebraic Approach I1

This paper is the first of the three parts of work on the information retrieval systems proposed by Salton (see [24]). The system is defined by the notions of a partially ordered set of requests (A, ⩽), the set of objects X and a monotonic retrieval function U : A → 2X. Different conditions imposed on the set A and a function U make it possible to obtain various classes of information retrieval systems. We will investigate systems in which (A, ⩽) is a partially ordered set, a lattice, a pseudo-Boolean algebra and Boolean algebra. In my paper these systems are called partially ordered information retrieval systems (po-systems) lattice information retrieval systems (l-systems); pseudo-Boolean information retrieval systems (pB-systems) and Boolean information retrieval systems (B-systems). The first part concerns po-systems and 1-systems. The second part deals with pB-systems and B-systems. In the third part, systems with a partial access are investigated. The present part discusses the method for construction of a set of attributes. Problems connected with the selectivity and minimalization of a set of attributes are investigated. The characterization and the properties of a set of attributes are given.