with the increase of the volume of information and the progress in technology, the deficiency of traditional algorithms for fast information retrieval becomes more clear. when large volumes of data are to be handled, the use of neural network as an artificial intelligent technique is a suitable method to increase the information retrieval speed. neural networks present a suitable representation...

qutb al-din mohammad known as abdoll?h-e-qutb, is the mystic and austere of 15-16 centuries whose most important trait of life is his plan of an ideal society organization, called “ekhvan-?b?d”. such a devotional aggregation near the city of jahrom, provoked high sensitivity and prompted disagreements, because of this period’s advent. since, after several centuries, there have been remained not...

Camera-captured document images usually contain two main types of marginal noise: textual noise (coming from neighboring pages) and non-textual noise (resulting from the page surrounding and/or binarization process). These types of marginal noise degrade the performance of the preprocessing (dewarping) of camera-captured document images and subsequent document digitization/recognition processes...

This paper describes a Japanese spoken document retrieval system that is robust for Out-of-Vocabulary (OOV) words. A standard approach to spoken document retrieval is to automatically transcribe spoken documents into word sequences, which can be directly matched against queries. In this approach, the documents including OOV words and words misrecognized as other words cannot be retrieved. To av...

Keywords characterize the topics discussed in a document. Extracting a small set of keywords from a single document is an important problem in text mining. We propose a hybrid structural and statistical approach to extract keywords. We represent the given document as an undirected graph, whose vertices are words in the document and the edges are labeled with a dissimilarity measure between two ...

We propose a multiple-document summarization system with user interaction that summarizes more than one document to a document. Our system extracts keywords from sets of documents to be summarized and shows k best keywords with respect to scoring by our system to a user on the screen. From the shown keywords, the user selects those reflecting the user's summarization need. Our system controls t...

In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one....