Paper Info
Title
Quality Indicators of LSP Texts - Selection and Measurements Measuring the Terminological Usefulness of Documents for an LSP Corpus
Abstract
This paper describes and evaluates a prototype quality assurance system for LSP corpora. The system will be employed in compiling a corpus of 11 M tokens for various linguistic and terminological purposes. The system utilizes a number of linguistic features as quality indicators. These represent two dimensions of quality, namely readability/formality (e.g. word length and passive constructions) and density of specialized knowledge (e.g. out-of-vocabulary items). Threshold values for each indicator are induced from a reference corpus of general (fiction, magazines and newspapers) and specialized language (the domains of Health/Medicine and Environment/Climate). In order to test the efficiency of the indicators, a number of terminologically relevant, irrelevant and possibly relevant texts are manually selected from target web sites as candidate texts. By applying the indicators to these candidate texts, the system is able to filter out non-LSP and "poor" LSP texts with a precision of 100% and a recall of 55%. Thus, the experiment described in this paper constitutes fundamental work towards a formulation of 'best practice' for implementing quality assurance when selecting appropriate texts for an LSP corpus. The domain independence of the quality indicators still remains to be thoroughly tested on more than just two domains.
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
quality assurance,two dimensions
Field
DocType
Citations 
Best practice,Domain independence,Information retrieval,Formality,Computer science,Newspaper,Readability,Speech recognition,Natural language processing,Artificial intelligence,Recall,Quality assurance
Conference
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Jakob Halskov151.17
Dorte Haltrup Hansen2144.58
Anna Braasch394.41
Sussi Olsen4137.71