Täistekstiindeksid

Täistekstiindeksid, known in English as full-text indexes, are data structures that enable efficient searching within large collections of text documents. They work by pre-processing a body of text and creating an inverted index. This inverted index maps individual words, or tokens, to the documents in which they appear. When a search query is entered, the system consults the inverted index to quickly identify all documents containing the query terms. This is significantly faster than performing a linear scan through every document for each search.

The process of creating a full-text index typically involves several steps. First, the text is tokenized, breaking it down into individual words or meaningful units. Punctuation is usually removed, and words may be converted to lowercase to ensure case-insensitive searching. Stop words, such as common articles and prepositions (e.g., "the," "a," "is"), are often filtered out as they are unlikely to be useful for distinguishing between documents. Stemming or lemmatization may also be applied to reduce words to their root form, allowing searches for variations of a word (e.g., searching for "run" would also find "running," "ran").

Full-text indexing is a fundamental technology behind search engines, database search functionalities, and document management systems. Its effectiveness lies in transforming unstructured text data into a searchable format, allowing users to retrieve relevant information with speed and accuracy. The size and complexity of the index can grow with the volume of text, and various optimization techniques are employed to manage these large-scale indexes efficiently.