stoppord

Stoppord, or stop words, are highly frequent words that typically carry little lexical meaning on their own but are essential for the grammar of a language. In many natural language processing and information retrieval tasks, these words are filtered out or given low weight to improve efficiency and focus on content-bearing terms.

Stop-word lists vary by language and domain. In Swedish and Norwegian, common stoppord include articles and function words such as och/og (and), i (in), det (it), att (to), som (which/that), är (is). In English examples include the, is, at, which, and. Lists are often hand-curated or generated statistically from large corpora.

Benefit and limitations: Removing stoppord reduces vocabulary size and speeds up indexing and search. It can improve precision in simple keyword search and topic modeling. However, it can also remove information essential for intent, syntax, or sentiment. For example, negations and certain pronouns can alter meaning; some tasks require keeping stop words, such as question answering or parsing dependencies.

Implementation: Most NLP libraries provide built-in stop-word lists and allows customization. Common approaches include stop-word removal during tokenization, or assigning low tf-idf weights to these terms rather than removing them outright. Domain-specific corpora may require tailored lists, balancing recall and precision.