Rank Aggregation techniques have found wide applications for metasearch along with other streams such as Sports, Voting System, Stock Markets, and Reduction in Spam. This paper presents the optimization of rank lists for web queries put by the user on different MetaSearch engines. A metaheuristic approach such as Genetic algorithm based rank…

Presents an interpolation theorem for an extended Boolean information retrieval model. Results show that whenever two or more documents are similarly ranked at any two points for a query containing exactly two terms, then they are similarly ranked at all points in between; and that results can fail for queries with more than two terms. (Author/LRW)

Investigates the problem of fusing collections of documents provided by multiple information retrieval systems. A parameterized approach is suggested in which a parameter determines how the documents in the individual collections are interleaved to form a fused list of documents. (Author/LRW)

Explains vocabulary mining in information retrieval and describes a framework for vocabulary mining that allows the use of rough set-based approximations even when documents and queries are described using weighted, or fuzzy, representations. Examines coordination between multiple vocabulary views and applies the framework to the Unified Medical…

Presents a general method to construct ordered similarity measures in information retrieval based on classical similarity measures for ordinary sets. Describes a test of some of these measures in an information retrieval system that extracted ranked document sets and discuses the practical usability of the ordered similarity measures. (Author/LRW)

Describes a string-searching algorithm for multiple patterns in a text string; explains the construction of a pattern-matching machine; presents a theoretical analysis and empirical evidence that supports the sublinearity of the algorithm; and compares this algorithm with the Boyer-Moore algorithm for a single pattern. (Contains 10 references.)…

Investigates the modeling of changes in user interest in information filtering systems and develops a new technique for tracking user interest shifts based on a Bayesian approach. Presents an analytical study to establish the rate of convergence for a profile learning module with and without the user interest tracking component. (Author/LRW)

Introduces a rotation and scale invariant log-polar wavelet texture feature for image retrieval. The underlying feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. Experimental results show that this rotation and scale invariant wavelet feature is quite effective for image…

Discusses latent semantic indexing (LSI) that would allow search engines to reduce the dimension of the document space by mapping it into a space spanned by conceptual indices. Topics include vector space models; singular value decomposition (SVD); unitary operators; the Haar transform; and new algorithms. (Author/LRW)

Explores aspects of data fusion (DF) for information retrieval (IR) using a set of data from the Fifth International Conference on Text Retrieval (TREC5). Derives an equation for effective DF based on a geometric model and shows that the performance of a pair of IR schemes may be approximated by a quadratic polynomial. (Author/LRW)

Discussion of information retrieval focuses on an Interaction Information Retrieval model in which documents are interconnected; queries and documents are treated in the same way; and retrieval is the result of the interconnection between query and documents. A theoretical mathematical formulation of this type of retrieval is given. (Contains 31…

Discussion of probabilistic information retrieval (IR) systems challenges the probability ranking principle in IR from the perspective of (1) signal detection-decision theory and (2) utility theory. Calibration, certainty, and independent assessment are discussed in terms of the relevance of documents, and standard retrieval policies are analyzed.…

Discussion of information-retrieval effectiveness focuses on the use of multiple query or document representations, or multiple retrieval techniques, and combining the retrieval results (also known as data fusion). Experimental results with the SMART System (developed at Harvard and Cornell Universities for over 38 years) indicate combining…

Describes SENTINEL, a prototype information-retrieval system that is a fusion of multiple information-retrieval technologies, integrating n-grams, a vector space model, and a neural network training rule. Discusses three-dimensional visualization capability, precision and recall, mathematical representation of a document, query building, and…

Presents a unified mathematical definition for the classical models of information retrieval and identifies a mathematical structure behind relevance feedback. Highlights include vector information retrieval; probabilistic information retrieval; and similarity information retrieval. (Contains 118 references.) (Author/LRW)