Sharif Digital Repository

One of the important issues in security fields is hidden exchange of information. There are different methods for this purpose such as cryptography and steganography. Steganography is a method of hiding data within a cover media so that other individuals fail to realize their existence. In this paper a new method for steganography in English texts is proposed. In this method the US and UK spellings of words substituted in order to hide data in an English text. For example "color" has different spelling in UK (colour) and US (color). Therefore the data can be hidden in the text by substituting these words  

In many real-world applications (e.g. social media application), data usually consists of diverse input modalities that originates from various heterogeneous sources. Learning a similarity measure for such data is of great importance for vast number of applications such as classification, clustering, retrieval, etc. Defining an appropriate distance metric between data points with multiple modalities is a key challenge that has a great impact on the performance of many multimedia applications. Existing approaches for multi-modal distance metric learning only offer point estimation of the distance matrix and/or latent features, and can therefore be unreliable when the number of training... 

Most email users have encountered with spam problems, which have been addressed as a text classification or categorization problem. In this paper, we propose a novel spam detection method that uses ensemble of classifiers based on clustering and selection techniques. There is diversity in genre of e-mail's content and this method can find different topics in emails by clustering. It first computes disjoint clusters of emails, and then a classifier is trained on each cluster. When new email arrives, its cluster is identified. The classifier of the identified cluster is selected to classify the new email. Our method can extract many kinds of topics in emails. The evaluation shows that the... 

In the last decade spam detection has been addressed as a text classification or categorization problem. In this paper we propose a new dynamic weighted voting method based on the combination of clustering and weighted voting, and apply it to the task of spam filtering. In order to classify a new sample, it first compares with all cluster centroids and its similarity to each cluster is identified; Classifiers in the vicinity of the input sample obtain greater weight for the final decision of the ensemble. The evaluation shows that the algorithm outperforms pure SVM. © 2008 IEEE  

Nowadays, OCR (Optical Character Recognition) is widely used for converting written documents to digital documents. One of the OCR phases is page segmentation. In page segmentation, text regions must be found in input image. In addition, text parts like text columns must be separated. In this paper, a new method for segmenting Persian/Arabic printed text is proposed. This method is based on Ink Spread Effect idea, a new idea that has particular features. Main features of Persian/Arabic scripts are considered in designing this method. This method is skew resistant and can segment text within frames and tables or regions with gray background. © 2006 ICASE  

Segmentation is a very important stage of Farsi/Arabie character recognition systems. A new segmentation algorithm -for multi font Farsi/Arabic texts- based on the conditional labeling of the up contour and down contour is presented. A pre-processing technique is used to adjust the local base line for each subword. This algorithm uses adaptive base line for each subword to improve the segmentation results. This segmentation algorithm, in addition to up and down contours, takes advantage of their curvatures also. The algorithm was tested on a data set of printed Farsi texts, containing 22236 characters, in 18 different fonts. 97% of characters were correctly segmented. © 2005 IEEE  

This paper presents a novel method for answering complex temporal ordering questions in the context of an event and query-based text summarization. This task is accomplished by precisely mapping the problem of "query-based summarization of temporal ordering questions" in the field of Natural Language Processing to "verifying a finite state model against a temporal formula" in the realm of Model Checking. This mapping requires specific definitions, structures, and procedures. The output of this new approach is promisingly a readable and informative summary satisfying the user's needs  

Nowadays, computer is being used in many aspects of human life. A consequence of computer is electronic documents. Computers can't understand written documents. So, we need to convert written documents to electronic documents in order to be able to process them with computers. One of the common methods for converting written texts to electronic text is Optical Character Recognition (OCR). A lot of work has been done on English OCR, but Persian/Arabic OCR is still under development. A phase which commonly used in recognition part of an OCR system is estimating font size of text. Usually when the font size of text is found, the pen width is calculated. The pen width can be used for character... 

Conveying information secretly and establishing hidden relationship has been of interest since long past. Text documents have been widely used since very long time ago. Therefore, we have witnessed different method of hiding information in texts (text steganography) since past to the present. In this paper we introduce a new approach for steganography in Persian and Arabic texts. Considering the existence of too many points in Persian and Arabic phrases, in this approach, by vertical displacement of the points, we hide information in the texts. This approach can be categorized under feature coding methods. This method can be used for Persian/Arabic Watermarking. Our method has been... 

The importance of good weighting methodology in information retrieval methods - the method that affects the most useful features of a document or query representative - is examined.. Weighting features is the thing that many information retrieval systems are regarding as being of minor importance as compared to find the feature and the experiments are confirming this. There are different methods for the term weighting such as TF*IDF and Information Gain Ratio which have been used in information retrieval systems, the paper provides a brief review of the related literature. This paper explores using GA for concept weighting which is a novel application to the field of text mining It proposes... 

Text processing, as one of the main issues in the field of artificial intelligence, has received a lot of attention in recent decades. Numerous methods and algorithms are proposed to address the task of semantic textual similarity which is one of the sub-branches of text processing. Due to the special features of the Persian language and its non-standard writing system, finding semantic similarity is an even more challenging task in Persian. On the other hand, producing a proper corpus that can be used for training a model for finding semantic similarities, is of great importance. In this study, the main purpose is to propose a method for measuring the semantic similarity between short... 

One of the main causes of death the world over are cardiovascular diseases, of which coronary artery disease (CAD) is a major type. This disease occurs when the diameter narrowing of one of the left anterior descending, left circumflex, or right coronary arteries is equal to or greater than 50 percent. Angiography is the principal diagnostic modality for the stenosis of heart vessels; however, because of its complications and costs, researchers are looking for alternative methods such as data mining. This study conducts data mining algorithms on the Z-Alizadeh Sani dataset which has been collected from 303 random visitors to Tehran's Shaheed Rajaei Cardiovascular, Medical and Research... 

In this paper, we present a new approach to localize a bug in the software source file hierarchy. The proposed approach uses log files of the revision control system and bug reports information in open bug repository of open source projects to train a Support Vector Machine (SVM) classifier. Our approach employs textual information in summary and description of bugs reported to the bug repository, in order to form machine learning features. The class labels are revision paths of fixed issues, as recorded in the log file of the revision control system. Given an unseen bug instance, the trained classifier can predict which part of the software source file hierarchy (revision path) is more... 

With the extensive growth in information, text classification as one of the text mining methods, plays a vital role in organizing and management information. Most text classification methods represent a documents collection as a Bag of Words (BOW) model and then use the histogram of words as the classification features. But in this way, the number of features is very large; therefore performing text classification faces serious computational cost problems. Moreover, the BOW representation is unable to recognize semantic relations between words. Recently, topic-model approaches have been successfully applied for text classification to overcome the problems of BOW. Our main goal in this paper... 

We present a novel corpus for automatic punctuation prediction in persian texts. punctuation prediction is an important task in automatic speech recognition (ASR). The output of ASR systems is typically a raw sequence of words with no punctuation marks; this makes the text difficult or even impossible to make sense of for humans and also for any text processing unit. In this work, we have assembled a state-of-the-art Persian corpus to train and test a punctuation prediction model. To the best of our knowledge, this is the first ever corpus specifically designed for punctuation prediction in Persian texts. The corpus is a modification of a manually part-of-speech (POS) tagged Persian one,...