Function

Static Public Summary
public	augmented(K: number): function doouble normalisation score functon generator K + (1-K) (count / max count)
public	binary(): number binary tf (1)
public	count(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number raw term count
public	async evaluate(system: System, parser: QueryParser, cases: object): object Evaluate an IR system.
public	extractObjectValues(document: object, fields: object, callback: function) extract values from a document object
public	inverseDocumentFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number idf - number of documents / number of documents with term
public	inverseDocumentFrequencyMax(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number idf max
public	inverseDocumentFrequencySmooth(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number idf smooth
public	logNormal(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number 1 + log(count)
public	naiveBayes(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number anonymous function - description
public	probabilisticInverseDocumentFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number probailistic idf
public	termFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number term frequency (raw cunt / total raw count)
public	unary(): number unary idf (1)

Static Public

public augmented(K: number): function source

import {augmented} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

doouble normalisation score functon generator K + (1-K) (count / max count)

Params:

Name	Type	Attribute	Description
K	number	optional default: 0.5	augment weight

Return:

function

score function

public binary(): number source

import {binary} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

binary tf (1)

Return:

number

calculated score

public count(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {count} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

raw term count

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public async evaluate(system: System, parser: QueryParser, cases: object): object source

import evaluate from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/evaluate.js'

Evaluate an IR system.

Params:

Name	Type	Attribute	Description
system	System		description
parser	QueryParser		description
cases	object		description

Return:

object

description

public extractObjectValues(document: object, fields: object, callback: function) source

import extractObjectValues from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/misc/extractObjectValues.js'

extract values from a document object

Params:

Name	Type	Attribute	Description
document	object		target document
fields	object		array of fields or map of fields to score
callback	function		callback function will be called for each value

public inverseDocumentFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {inverseDocumentFrequency} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

idf - number of documents / number of documents with term

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public inverseDocumentFrequencyMax(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {inverseDocumentFrequencyMax} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

idf max

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public inverseDocumentFrequencySmooth(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {inverseDocumentFrequencySmooth} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

idf smooth

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public logNormal(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {logNormal} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

1 + log(count)

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public naiveBayes(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {naiveBayes} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

anonymous function - description

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public probabilisticInverseDocumentFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {probabilisticInverseDocumentFrequency} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

probailistic idf

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public termFrequency(t: number, sum_t: number, max_t: number, sum_dt: number, sum_all: number, count_d: number, count_dt: number, max_dt: number): number source

import {termFrequency} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

term frequency (raw cunt / total raw count)

Params:

Name	Type	Attribute	Description
t	number		number of times term occurs in document
sum_t	number		sum of t for all terms in document
max_t	number		maximum number of times any term occurs in document
sum_dt	number		total number of terms in document
sum_all	number		total number of terms in document collection
count_d	number		total number of documents
count_dt	number		total number of documents with term
max_dt	number		maximum number of documents per term

Return:

number

calculated score

public unary(): number source

import {unary} from 'information-retrieval-boilerplate/node-information-retrieval-boilerplate/src/scores/index.js'

unary idf (1)

Return:

number

calculated score