The 9th annual WTLab Workshop
- Last Updated on Tuesday, 16 April 2019 12:15
The 9th annual workshop of WTlab of Ferdowsi, University of Mashhad, simultaneous with 8th International Conference on Computer and Knowledge Engineering (ICCKE 2018) will be held at October the 23rd and 24th.
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.
Getting to know Social Network analysis tools
Nowadays, many people use social network capabilities to connect with others or share news or their favorite topic. Big volume of data consists of user interactions with each other which have encouraged researchers to discover knowledge from them. This information can be divided into three categories: Textual information, Linked Information and Time Information. Since users generate Textual content more, textual data plays a more important role in knowledge discovery from social networks. The purpose of this workshop is to introduce social networks and how to use different kinds of information in them to solve real-life problems.
Roles of the social network in practical applications
Challenges of processing social networks data and their solution
Hot research areas in social networks
Social network analysis tools
Detecting leader nodes in a social network
Detecting bridge nodes in a social network
Detecting Inflectional spreader in social network
Finding K nearest neighbor for a node
Finding shortest paths between several nodes in a graph
Clustering and community detection in graph
Pajek software input file format
Igraph, one of R’s packages and how to use it
D3, a tool for presenting graph and how to use it with Network D3 in R
- Maryam Khodabakhsh
- Ramin Rezvani
October the 24th,2018
introducing text mining methods and its programming tools in python
The volume of textual data is growing dramatically. This big volume of text is usually unstructured and therefore, can’t be easily processed with a computer. Thus, practical techniques and algorithms are needed to detect structure, information and useful patterns inside the text. Text mining is a set of methods which extract meaningful information from a text. In this workshop, we will introduce some of the basic techniques for text mining such as textual preprocessing, classification and clustering, and then, we will give a general review of python’s different libraries for text mining and study some source codes as examples for each of these tools.
Introduction to text mining
Methods for text pre-processing
Knowledge extraction methods
Introduction to some of Pythons libraries for text mining (Polyglot, TextBlob, NLTK, Pattern, Gensim, spaCy and etc.)
Examples of how to Code with each library
October the 25th, 2018