TR@KNTU: a research group @ K. N. T. U

Nowadays, we are faced with a data explosion on the web. The data are electronically distributed and are represented in different formats. The hardness is to find a relative few truly relevant information from the wide number of identified resources.

The Text Retrieval research Group at K. N. Toosi University of Technology is a team of faculty, students, and programmers who work together on algorithms that allow computers to retrieve and process texts extracted from web and social media. Our work is in the areas of information retrieval, data mining, social network analysis, and applied machine learning on large-scale web data, with applications to search engines, sentiment mining, and text analytics.

Information Retrieval: Ranking models, query expansion, query suggestion, query auto-completion, web search optimization.

Learning to Rank:  Dynamic online ranking evaluation for web search using online learning from machine learning.

Web Science: Emerging challenges in web-mediated data exchange, such as social media platforms and archiving initiatives.

Text Analytics: Topic, aspect, and trend mining from the web and social networks using graph, statistical and linguistic analysis.

Deep Learning for Text: LSTM, Stacked autoencoders, Recurrent neural networks for text understanding and retrieval.

Social Network Analysis: Community detection, trend detection, and so on.


In the following, some IR/NLP labs are hyperlinked.

Stanford University

Illinois Institute of Technology

University of Copenhagen

University of Amsterdam

Cornell University

Carnegie Mellon University

University of Texas at Austin

Simon Fraser University

University of Washington

University of California

University of Queensland

University of Toronto

University of Massachusetts Amherst