Stopwords in Technical Language Processing
This work provides a domain-specific tool for improving NLP applications like information retrieval and topic modeling in engineering contexts, though it is incremental as it adapts existing stopword methods to a new domain.
The paper tackled the lack of a standard stopword list for engineering texts by identifying and curating a new list of stopwords specific to technical jargon, addressing the gap in existing general English lists.
There are increasingly applications of natural language processing techniques for information retrieval, indexing and topic modelling in the engineering contexts. A standard component of such tasks is the removal of stopwords, which are uninformative components of the data. While researchers use readily available stopword lists which are derived for general English language, the technical jargon of engineering fields contains their own highly frequent and uninformative words and there exists no standard stopword list for technical language processing applications. Here we address this gap by rigorously identifying generic, insignificant, uninformative stopwords in engineering texts beyond the stopwords in general texts, based on the synthesis of alternative data-driven approaches, and curating a stopword list ready for technical language processing applications.