The 10th annual WTLab Workshop
- Last Updated on Monday, 21 October 2019 11:12
The 10th annual WTLab Workshop
The 10th annual workshop of WTlab of Ferdowsi, University of Mashhad, simultaneous with 9th International Conference on Computer and Knowledge Engineering (ICCKE) will be held on November 2nd and 3rd.
Phone: 05138806163
Email: Wtlab@um.ac.ir
To register click here. (registration is open until november 1st)
Attention: The workshop will be held at the decided time virtually , Also certification of attendance is given to the audience by the university, thus, please be prices about address when you are registering.
Multi Agent Programming
Abstract
In recent years, the use of cognitive models for designing and developing agents to simulate real scenarios has gained the attention of many researchers and programmers. The main benefit of these models is that their logic is close and similar to human’s problem-solving methods. One of the recommended cognitive models is the belief-desire-intension model. In this workshop, in addition to discussing this model, we introduce The Jadex tool, which supports this model. In the end, we will design a problem using this model and then will solve it by programming in Jadex.
In the second part of the workshop, we will introduce a modeling technique to analyze complicated problems. Using modeling, we can significantly reduce the costs of testing in a real environment. There are many software that are developed with the help of intelligent agents to help with simulation and solving problems. In this workshop, we will discuss the functions and features of Netlogo. This part of the workshop is about getting to know the main components of Netlogo and the presentation of some basic examples.
Headlines
Introduction to BDI cognitive model
Introduction to Jadex and problem solving
Principles of modeling in Netlogo
Research Area
Providers
- Reza Saeedi
- Seyed Ahmad Tousi
Present Type
Virtual
Holding Time
Date:November the 2nd
Time:8 To 12
Duration
4 hours
Files
Natural Language Processing
Abstract
The main effort in NLP is to mechanize the process of understanding the concept presented by a natural language. With computer technology entering our lives, language and common conversation processing are two of the tasks that have attracted the attention of many scientists. The main goal in NLP is to create computational theories of language, using algorithms and data structure available in computer science. To perform many processes on languages such as translation, summarization, spell correction, etc. automatically, we need some tools to preprocess and prepare the text.
Nowadays there is a huge volume of textual data on the web. To use them some processing needs to be done so that the knowledge within them can be extracted. Processing information can be done in three levels, lexical, semantic and syntactic. In this workshop, we will talk about programming for these three types of processing.
Headlines
Headlines for the first part of the workshop
Introductory concepts
A review on NLP applications
Levels of NLP
A glance over NLP tools in the Persian language
NLP activists in Iran
Developed and available tools for Persian NLP
Some example of Persian NLP tools’ usage
The challenges of Persian NLP and the limitations of this field in Iran
Headlines for the second part of the workshop
A summarized review of theoretical NLP concepts (lexical, semantic, syntactic)
NLP programming for lexical text processing using Stanford library
NLP programming for syntactical text processing (parser and co-reference) using Stanford library
Programming method to connect to link extraction tools such as DBpedia, Spotlight, and TAGme
Programming method to connect to and extract from Wordnet
Programming method to perform a query on linked cloud data using previous processes
Research Area
Providers
Present Type
Virtual
Holding Time
Date:November the 2nd
Time:14 To 18
Duration
4 hours
Files
Process Mining
Abstract
Process mining is a new research field that has gained a lot of attention in recent years. This field is a combination of computational intelligence, data mining, modeling and analyzing processes. The purpose of process mining is to discover, monitor and improve real processes using the extracted knowledge from stored data in available information systems. It can be utilized in industries, banks, insurances, hospitals, municipality, university, etc. in this workshop we will introduce process mining, its challenges, similarity detection methods and applications of process mining and will talk about the tools that can be used in this field.
Headlines
Introduction to process mining
Challenges of process mining
Applications of process mining
Introduction to process mining tools
Research Area
Providers
- Fatemeh Khojasteh
- Jalal Sakhdari
Present Type
Virtual
Holding Time
Date:November the 3th
Time:8 To 12
Duration
4 hours
Files
Social Network Analysis
Abstract
Nowadays many people use the features in various social networks as one of the most popular communication tools to communicate with each other and share news or their subjects of interest. The huge volume of data of users’ behavior and interaction with each other has acted as encouragement for researchers to discover knowledge. The information in social networks can be categorized into three: textual data, linked data and time data. Since more of the data generated by the users are text, textual data plays an important role in discovering knowledge in social networks. The purpose of this workshop is to introduce social networks and the way we can use different information in them to solve real-world problems. Also, a variety of tools to analyze this information and interpret the output will be introduced in this workshop.
Headlines
The role of social networks in application
The challenges of social networks’ data processing and their solutions
Hot research fields of social networks
A review on social network analysis tools
Introduction to Pajek
Introduction to IGraph
Introduction to NetworkX
Centrality
Leader node detection in social network
Bridge node detection in social network
Influential spreader node (effective in message propagation) detection in social network
Finding K nearest neighbor for a node
Finding the shortest path between nodes in a graph
Clustering and community detection in graph
The D3 tool for graph presentation
Research Area
Providers
- Maryam Khodabakhsh
- Ramin Rezvani
Present Type
Virtual
Holding Time
Date:November the 3th
Time:14 To 18
Duration
4 hours
Files