TDM In Information Retrieval

The use of text and data mining technologies, such as information extraction and knowledge representation, to improve the performance of information retrieval systems or to enable the application of information retrieval system to new tasks beyond document retrieval.

Resources

Intended audience Policy makers and Funders, Programmers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial describes how to use TDM to build a Recommender system for scholarly resources and utilise OpenMinTed platform to build and annotate corpuses for this purpose.

By  Florian Leitner
By  Zakaria Kehel, Jose Crossa, Thomas Payne, Matthew Reynolds
By  Fabrizio Celli, Thembani Malapela, Karna Wegner, Johannes Keizer
By  Fabrizio Celli, Johannes Keizer, Yves Jaques, Stasinos Konstantopoulos, Dušan Vudragović
By  Hesha J. Duggirala, Joseph M. Tonning, Ella Smith, Roselie A. Bright, John D. Baker, Robert Ball, Carlos Bell, Khaled Bouri, Susan J. Bright-Ponte, Taxiarchis Botsis, Ma rc Boyer, Keith Burkhart, G. Steven Condrey, James J. Chen, Stuart Chirtel, Ross W. Filice, Henry Francis, Hongying Jiang, Jonathan Levine, David Martin, Taiye Oladipo, Rene O’ Neill, Lee Anne M. Palmer, Antonio Paredes, George Rochester, Deborah Sholtes, Hui- Lee Wong, Zhiheng Xu, Ana Szarfman, Taha Kass -Hout