Community detection is an important aspect in discovering the complex structure of social networks, and is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. A social network graph is a representation of the real world social network with the nodes representing the participating entities, or in this case, research papers or their authors, and the relations between these entities are represented by edges between them. Community detection involves grouping of similar users into clusters, where users in a group are strongly bonded with each other than the other members in the network.
In this project, “Community Detection from Research Articles”, the task is to detect research papers that belong to a common field of research.
- Code: https://goo.gl/CXej44
- Youtube video: https://goo.gl/SCpamf
- Slideshare PPT: http://goo.gl/XzOZdC
- Dropbox (Report, PPT, Video): https://goo.gl/cgACzU
Information Retrieval and Extraction Course