Information Processing and Management: an International Journal - The Potential for Improvments in Commerical Document Retrieval Systems
Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Signals & systems (2nd ed.)
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Introduction to Algorithms
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
Fourier Domain Scoring: A Novel Document Ranking Method
IEEE Transactions on Knowledge and Data Engineering
The Geometry of Information Retrieval
The Geometry of Information Retrieval
A novel document retrieval method using the discrete wavelet transform
ACM Transactions on Information Systems (TOIS)
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
Digital Signal Processing
A probability ranking principle for interactive information retrieval
Information Retrieval
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
Recommender systems by means of information retrieval
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Scaling up high-value retrieval to medium-volume data
IRFC'10 Proceedings of the First international Information Retrieval Facility conference on Adbances in Multidisciplinary Retrieval
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Information Retrieval (IR) systems combine a variety of techniques stemming from logical, vector-space and probabilistic models. This variety of combinations has produced a significant increase in retrieval effectiveness since early 1990s. Nevertheless, the quest for new frameworks has not been less intense than the research in the optimization and experimentation of the most common retrieval models. This paper presents a new framework based on Discrete Fourier Transform (DFT) for IR. Basically, this model represents a query term as a sine curve and a query is the sum of sine curves, thus it acquires an elegant and sound mathematical form. The sinusoidal representation of the query is transformed from the time domain to the frequency domain through DFT. The result of the DFT is a spectrum. Each document of the collection corresponds to a set of filters and the retrieval operation corresponds to filtering the spectrum – for each document the spectrum is filtered and the result is a power. Hence, the documents are ranked by the power of the spectrum such that the more the document decreases the power of the spectrum, the higher the rank of the document. This paper is mainly theoretical and the retrieval algorithm is reported to suggest the feasibility of the proposed model. Some small-scale experiments carried out for testing the effectiveness of the algorithm indicate a performance comparable to the state-of-the-art.