Sharif Digital Repository

Conversation modeling is one of the most important goals in the field of understanding natural language and machine intelligence. Recently, with the enormous growth of the Internet and social networks, the amount of available data on the Web has increased significantly.This makes it possible to use data-driven approaches to solve the modeling problem of conversation.One of the most recent data-driven methods is the sequence to sequence modeling. In this document, after providing the necessary prerequisites, we examined the various models that have used the sequence to sequence approach for conversation modeling. We further examined the ways of improving the efficiency of this modeling... 

In the extensive horizon of artificial intelligence technology, one of the grand challenges in computer vision has been semantic segmentation. This task which aimed to predict label for each pixel of image, describes the scene, due to the need of low level information, is more complicated in comparison with other computer vision tasks. However, as part of concept of scene understanding and a crucial step in many real world applications such as autonomous driving, human-computer interaction and robot navigation, many researchers have been sought to resolve it. What makes this task more challenging rather than other computer vision tasks is that information beyond a pixel, its neighbors and... 

In recent years, deep neural networks have achieved significant improvements in the field of automatic text summarization by using neural sequence architectures. However,the results of these improvements are more tangible in the production of short summaries (a few words or single sentences). In the field of producing long (multisentence) abstracts, the presented models suffer from several issues; These models produce the details of the events incorrectly and tend to generate the phrases been produced before repeatedly. The wording from the output of these models is very close to the original text. Also, the metrics used to evaluate the quality of produced summaries do not have the ability... 

Cryptocurrencies are not only regarded as a trustworthy method of financial transaction validated by a decentralized cryptographic system as opposed to a centralized authority, but also as one of the most popular and lucrative forms of trade and investing. Predicting the price of a cryptocurrency is a challenging topic in time-series research. Its intricacy is due to the volatility and large swings of cryptocurrencies' price. The emergence of brand-new cryptocurrencies, which might present a profitable trading opportunity but lack sufficient historical data for technical analysis, prompted us to develop a trading strategy that could be applied universally. The forecast of the next timestep's... 

Design and production of a drug is a very time and money consuming process. It takes more than a decade and about 2.5 million dollars on various stages to design a drug. Attempts to reduce this cost and time to market will make drugs available to customers at a more reasonable time. Some stages such as animal testing phase and clinical trials, can not be replaced and must take place in practice. Fortunately, some laboratory steps are interchangeable with software algorithms. These algorithms can significantly reduce the cost and time to market of the drug if they are accurate enough. On the other hand, the remarkable results of machine learning, in particular, Deep Neural Networks, in areas... 

Around world and the networks within it can be modeled in various templates. Graph structure is one of those templates in which objects and relations may have more than one types. We call this phenomenon "heterogeneity".Heterogeneity makes the networks hard to model and that is why the proposed methods for modeling the networks assumed the network structures homogeneous. This assumption may cause data loss due to ignoring the variety of types in network objects and relations and this loss can lessen the accuracy of data mining tasks.To tackle the challenge of data loss in the mentioned assumption, learning representations for heterogeneous information networks (HINs) was introduced. HINs... 

Today, with the increasing proliferation of digital tools, manipulating digital images has become a simple matter. Therefore, in many cases related to Forensics, issues related to the intellectual property, we need to verify the authenticity of the images. There are different types of image manipulation, but image splicing manipulation is the most frequent among the types of manipulations due to its simplicity and availability.In many applications, in addition to detection, the localization of the manipulated part, which is considered segmentation at the pixel level, is also of great importance.In this project, by using a structure based on deep encoder networks, a method for improving the... 

In the last three years, the lives of many people around the world have changed with the spread of the Corona virus. In order to better manage the consequences related to the spread of this disease, extensive research has been done on this virus, and researchers in data science and artificial intelligence have devoted a part of their research to studying the effects of this virus on the people in one or different societies.On the other hand, the study of social networks about a specific issue or trend topic, allows us to examine more closely the atmosphere that governs the society and analyze the emotions, feelings and the level of concern of the members of the society about that issue.The...