Sharif Digital Repository

Network forensic analysts employ Payload Attribution Systems (PAS) as an investigative tool. With such tool large amount of network traffic, including full packet payload, is summarized and stored. Hence an investigator could query the system for a specific string and see whether any packets transmitted previously in the network contained that specific string. Wildcards are an important type of query that allows the investigator to locate strings in the payload when only part of the string is known. In this thesis we present a new payload attribution technique, named character based bloom filter, which in addition to improving on previously proposed techniques is able to support wildcard... 

The news headlines should represent the main and the most important topics of their stories. The task of selecting an appropriate headline for news stories is mainly done by journalists. The goal of this project has been the design and implementation of a system to automate this task, that is generating headlines for news. This task has been done for Persian news stories. There are various methods for automatic headline generation in English and some other languages, but no work has been done for Persian, yet. Thus, we have adopted some of the ideas from those methods, and do the remaining by our initiation. Our proposed method consists of three main parts: keyword extraction, most important... 

With the rapid development in information-communication technologies a huge amount of electronic documents has been produced and increase everyday in the world wide web. According to this wide information environment, summarization is critical for the users who digest this electronic big data. This research proposes two graph-based abstractive models for summarizing the Persian texts. A good summary should cover the overall context and the important subjects, and should be properly readable and coherent as well. Some permanent challenges in automatic text summarizations intended to increase the readability of output text, as well as covering all the main topics, and minimize the redundancy.... 

Improvement of automatic speech recognition systems and the growth of audio data (such as broadcast news, voice mail, telephony conversations and meetings) have attracted plenty of research interest in the field of speech summarization. The goal of this dissertation is to improve the performance of the speech summarization in the domain of multi-party conversations, specifically meetings. Most of the previous work in this field are inheritted from the text summarization counterpart, whithout paying much attention to the discourse specific information of the multi-party conversations. The main idea of this work is to use discourse information to improve the accuracy of extracted summaries in... 

Graphs are widely used for representing structured data and analysis of them is an important area that appears in a broad domain of applications. Graph processing is of great importance in analyzing and predicting social media users' behavior, examining financial markets, detecting malware programs, and designing recombinant drugs. For example, consider a graph in which nodes and edges show the financial institutions and the financial connection between these institutions, respectively. Financial connection refers to the investment of one institute by another. Based on the graph structure, predicting trade stability and balance is extremely significant in macro decisions.In the last few...