Rank by Text BM25

Ranks objects in SOURCE [OBJ,STRING] according to the relevance score of each STRING with keywords in QUERY [STRING]. The relevance is computed using Okapi BM-25 ranking method.

• SOURCE [OBJ,STRING]: a 2-column input with an object-string pair. Typically obtained with the Extract string block
• QTERMS [STRING]: a list of keywords to rank SOURCE objects against

• RETRIEVE [OBJ]: a list of ranked objects

• 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 a QTERMS entry match a string in SOURCE are considered a match (AND logic for terms)
• One query per QTERMS row: if set to true, each row in QTERMS is considered as a separate query. All queries contributions are summed up (OR logic for queries)
• k1: controls non-linear term frequency normalization (saturation). Lower value = quicker saturation (term frequency is more quickly less important)
• b: degree of document-length normalization applied. 0=no normalization, 1=full normalization

Output scores can be normalized.