Evaluating a Text Mining Based Educational Search Portal
Sophia Ananiadou | John McNaught | James Thomas | Mark Rickinson | Sandy Oliver
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
In this paper, we present the main features of a text mining based search engine for the UK Educational Evidence Portal available at the UK National Centre for Text Mining (NaCTeM), together with a user-centred framework for the evaluation of the search engine. The framework is adapted from an existing proposal by the ISLE (EAGLES) Evaluation Working group. We introduce the metrics employed for the evaluation, and explain how these relate to the text mining based search engine. Following this, we describe how we applied the framework to the evaluation of a number of key text mining features of the search engine, namely the automatic clustering of search results, classification of search results according to a taxonomy, and identification of topics and other documents that are related to a chosen document. Finally, we present the results of the evaluation in terms of the strengths, weaknesses and improvements identified for each of these features.