Match by BM25

Description

This is a multi-query BM25 block, multiple lists of query keywords instead of a single one. It is in fact equivalent to a matching operation. It finds matches between the STRING-columns in the inputs by calculating the BM25 relevance score.

Input

Because this is originally a retrieval block, the notation SOURCE / QTERMS will be used, instead of A / B as in other matching blocks.

  • SOURCE [OBJ,STRING]: a list of candidates, in which the STRING-column will be used for comparison and the OBJ-column will be the result

  • QTERMS [OBJ,STRING]: a list of candidates, in which the STRING-column will be used for comparison and the OBJ-column will be the result

Output

  • RESULT [OBJ,OBJ]: the matched objects from SOURCE and QTERMS

Parameters

  • Stemming: tokens can be stemmed for a specific language or left as they are

  • Case-sensitive: if set to false, upper/lower case is ignored

  • Normalize diacritics: transliterates non-ASCII characters into their closest ASCII form

  • Tokenization: the method to tokenize the input strings.

    • None: perform no tokenization

    • Spaces: all valid Unicode space characters

    • Spaces/Punctuation: Spaces + all valid Unicode punctuation characters

    • Spaces/Punctuation/Digits: Spaces/Punctuation + all valid Unicode digit characters

    • Spaces/Punctuation/Digits/Symbols: Spaces/Punctuation/Digits + all valid Unicode symbol characters

    • Custom Regular Expression: any regular expression

  • Min token length: tokens whose character length is shorter than this value are discarded

  • Gram type:

    • Word (default): each token is composed by UTF-8 word n-grams

    • Character: each token is composed by UTF-8 character n-grams

  • Grams: allows to extract n-gram tokens (default is 1)

  • All query terms must match: if set to true, only candidates where all tokens in QTERMS match a string in SOURCE are considered a match

  • k1: controls non-linear term frequency normalisation (saturation). Lower value = quicker saturation (term frequency is more quickly less important)

  • b: degree of document-length normalisation applied. 0=no normalisation, 1=full normalisation