Sharif Digital Repository

The use of named entity recognition systems as preprocessing is used in many natural language analysis issues. With the advent of deep learning, the methods of this area were also affected. Today, there is considerable progress in this area due to the development of data resources for English, Chinese, German, and Spanish. They are also good trained models in formal Persian. However, for informal Persian, which contains a large portion of the web content under the Web, the current models do not produce a suitable solution. In this study, we use the same approach to train our models due to achieving state-of-the-art results in pre-trained models. On the other hand, there is a lack of standard... 

A large number of machine learning problems are considered as structured output problems in which the goal is to find the mapping function between an input vector to a number of variables in the output side which are statistically correlated. Motivated by the advantages of simultaneous learning of these variables compared to learning them separately, many structured output models have been introduced. Decreasing the sample complexity, increasing the generalization ability and overcoming to noisy data are some of these benefits. So in the first step of this research we concentrate on one of classical but important problems in bioinformatics which is automatic protein function prediction.... 

In order to survive in today's business world, which is changing at a very fast pace, organizations can detect deviations even before they occur, quickly and with a high percentage of confidence, by analyzing their processes, in order to prevent disruptions in the processes. by monitoring the information systems that automatically execute business processes, it is possible to ensure the correct implementation of the existing processes. For this purpose, various techniques for monitoring business processes have been presented so that managers have a comprehensive and real view of how implement processes and be able to identify possible deviations in the future and try to fix them because the... 

Effective tracking and re-identification of persons is essential for analyzing team sport videos. However, this task is challenging due to the nonlinear motion of players, the similarity in appearance of players from the same team, the distance of the camera from the persons on the pitch, and frequent occlusions. Therefore, the ability to extract meaningful embeddings to represent persons is crucial in developing an effective tracking and re-identification system. In team sports, there is other information that can be used for re-identification of persons, such as team affiliation, role information, and jersey number. However, existing methods usually suffer from two problems: first,...