formulation

package
v0.0.0-...-b7c488f Latest Latest
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 Go to latest Published: Dec 2, 2021 License: MIT Imports: 46 Imported by: 2

Documentation

Overview

Package formulation provides a library for automatically formulating queries.

Index

Constants

View Source 
const (
	NA    leaf = 0
	TRUE       = 1
	FALSE      = -1
)
View Source 
const Entity = "entity"

Variables

View Source 
var (
	/*
		#1 randomized controlled trial [pt]
		#2 controlled clinical trial [pt]
		#3 randomized [tiab]
		#4 placebo [tiab]
		#5 drug therapy [sh]
		#6 randomly [tiab]
		#7 trial [tiab]
		#8 groups [tiab]
		#9 #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8
		#10 animals [mh] NOT humans [mh]
		#11 #9 NOT #10
	*/
	SensitivityFilter = cqr.NewBooleanQuery(cqr.NOT, []cqr.CommonQueryRepresentation{
		cqr.NewBooleanQuery(cqr.OR, []cqr.CommonQueryRepresentation{
			cqr.NewKeyword("randomized controlled trial", fields.PublicationType),
			cqr.NewKeyword("controlled clinical trial", fields.PublicationType),
			cqr.NewKeyword("randomized", fields.TitleAbstract),
			cqr.NewKeyword("placebo", fields.TitleAbstract),
			cqr.NewKeyword("drug therapy", fields.FloatingMeshHeadings),
			cqr.NewKeyword("randomly", fields.TitleAbstract),
			cqr.NewKeyword("trial", fields.TitleAbstract),
			cqr.NewKeyword("groups", fields.TitleAbstract),
		}),
		cqr.NewBooleanQuery(cqr.NOT, []cqr.CommonQueryRepresentation{
			cqr.NewKeyword("animals", fields.MeshHeadings),
			cqr.NewKeyword("humans", fields.MeshHeadings),
		}),
	})

	/*
		#1 randomized controlled trial [pt]
		#2 controlled clinical trial [pt]
		#3 randomized [tiab]
		#4 placebo [tiab]
		#5 clinical trials as topic [mesh: noexp]
		#6 randomly [tiab]
		#7 trial [ti]
		#8 #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7
		#9 animals [mh] NOT humans [mh]
		#10 #8 NOT #9
	*/
	PrecisionSensitivityFilter = cqr.NewBooleanQuery(cqr.NOT, []cqr.CommonQueryRepresentation{
		cqr.NewBooleanQuery(cqr.OR, []cqr.CommonQueryRepresentation{
			cqr.NewKeyword("randomized controlled trial", fields.PublicationType),
			cqr.NewKeyword("controlled clinical trial", fields.PublicationType),
			cqr.NewKeyword("randomized", fields.TitleAbstract),
			cqr.NewKeyword("placebo", fields.TitleAbstract),
			cqr.NewKeyword("clinical trials as topic", fields.MeshHeadings).SetOption(cqr.ExplodedString, false),
			cqr.NewKeyword("randomly", fields.TitleAbstract),
			cqr.NewKeyword("trial", fields.Title),
		}),
		cqr.NewBooleanQuery(cqr.NOT, []cqr.CommonQueryRepresentation{
			cqr.NewKeyword("animals", fields.MeshHeadings),
			cqr.NewKeyword("humans", fields.MeshHeadings),
		}),
	})
)

Functions

func EntityExpansion 

func EntityExpansion(query cqr.CommonQueryRepresentation, expander EntityExpander) (cqr.CommonQueryRepresentation, error)

EntityExpansion performs entity expansion on a query using a specified expander.

func Entropy 

func Entropy(positive, negative float64) float64

func FilterQueryTerms 

func FilterQueryTerms(conditions, treatments, studyTypes []string, field string, development trecresults.Qrels, e stats.EntrezStatisticsSource) ([]string, []string, []string, error)

FilterQueryTerms reduces further query TermStatistics by identifying the best combination of TermStatistics based on how many relevant documents they retrieve from the development set.

func ID3 

func ID3(training map[string][]string, labels map[string]bool, attrs []string) *tree

func InformationGain 

func InformationGain(attr string, training map[string][]string, labels map[string]bool) (float64, []string, []string)

func MakeQrels 

func MakeQrels(docs []guru.MedlineDocument, topic string) trecresults.Qrels

MakeQrels creates a set of relevance assessments from some medline documents.

func MapKeywords 

func MapKeywords(r cqr.CommonQueryRepresentation, mapper KeywordMapper) (cqr.CommonQueryRepresentation, error)

MapKeywords takes as input a proto-query from a newly logically composed query and maps concepts in it to keywords using the specified mapper.

func RelevanceFeedback 

func RelevanceFeedback(query cqr.CommonQueryRepresentation, docs guru.MedlineDocuments, mm metawrap.HTTPClient) (cqr.CommonQueryRepresentation, error)

Types

type BackgroundCollection 

type BackgroundCollection interface {
	Statistic(term string) (float64, error)
	Size() (float64, error)
}

func GetPopulationSet 

func GetPopulationSet(e stats.EntrezStatisticsSource, analyser TermAnalyser) (BackgroundCollection, error)

GetPopulationSet retrieves a set of publications to form a population set.

type ConceptualFormulator 

type ConceptualFormulator struct {
	LogicComposer
	EntityExtractor
	EntityExpander
	KeywordMapper

	FeedbackDocs []int
	// contains filtered or unexported fields
}

ConceptualFormulator formulates queries using the title or string of a systematic review.

func NewConceptualFormulator 

func NewConceptualFormulator(logicComposer LogicComposer, entityExtractor EntityExtractor, entityExpander EntityExpander, keywordMapper KeywordMapper, rf []int, e stats.EntrezStatisticsSource, postProcessing ...PostProcess) *ConceptualFormulator

func (ConceptualFormulator) Formulate 

func (t ConceptualFormulator) Formulate(query pipeline.Query) ([]cqr.CommonQueryRepresentation, []pipeline.SupplementalData, error)

func (ConceptualFormulator) Method 

func (t ConceptualFormulator) Method() string

type Cui2VecEntityExpander 

type Cui2VecEntityExpander struct {
	// contains filtered or unexported fields
}

Cui2VecEntityExpander expands entities using cui2vec embeddings.

func NewCui2VecEntityExpander 

func NewCui2VecEntityExpander(embeddings cui2vec.PrecomputedEmbeddings) *Cui2VecEntityExpander

func (Cui2VecEntityExpander) Expand 

func (c Cui2VecEntityExpander) Expand(keyword cqr.Keyword) ([]cqr.CommonQueryRepresentation, error)

type Cui2VecRPCEntityExpander 

type Cui2VecRPCEntityExpander struct {
	// contains filtered or unexported fields
}

Cui2VecEntityExpander expands entities using cui2vec embeddings.

func NewCui2VecRPCEntityExpander 

func NewCui2VecRPCEntityExpander(client *cui2vec.VecClient) *Cui2VecRPCEntityExpander

func (*Cui2VecRPCEntityExpander) Expand 

func (c *Cui2VecRPCEntityExpander) Expand(keyword cqr.Keyword) ([]cqr.CommonQueryRepresentation, error)

type DecisionTreeFormulator 

type DecisionTreeFormulator struct {

	// Terms identified as candidate query terms.
	N [][]string // Attributes.
	// contains filtered or unexported fields
}

func NewDecisionTreeFormulator 

func NewDecisionTreeFormulator(topic string, positive, negative guru.MedlineDocuments) (*DecisionTreeFormulator, error)

func (DecisionTreeFormulator) Formulate 

func (dt DecisionTreeFormulator) Formulate(query pipeline.Query) ([]cqr.CommonQueryRepresentation, []pipeline.SupplementalData, error)

func (DecisionTreeFormulator) Method 

func (dt DecisionTreeFormulator) Method() string

type EntityExpander 

type EntityExpander interface {
	Expand(q cqr.Keyword) ([]cqr.CommonQueryRepresentation, error)
}

EntityExpander takes as input a keyword that has been annotated with entities in the entity extraction step and expands it.

type EntityExtractor 

type EntityExtractor interface {
	Extract(query cqr.CommonQueryRepresentation) (cqr.CommonQueryRepresentation, error)
}

EntityExtractor extracts entities from queries. These could be, for example, CUIs. Each Entity Extractor implementation adds the Entity option on queries which is used later in the keyword mapping step.

type Formulator 

type Formulator interface {
	Formulate(query pipeline.Query) ([]cqr.CommonQueryRepresentation, []pipeline.SupplementalData, error)
	Method() string
}

Formulator formulates queries to some specification.

type KeywordMapper 

type KeywordMapper interface {
	Map(keyword cqr.Keyword) ([]cqr.CommonQueryRepresentation, error)
}

KeywordMapper transforms entities (e.g., CUIs into keywords).

type LogicComposer 

type LogicComposer interface {
	Compose(query pipeline.Query) (cqr.CommonQueryRepresentation, error)
}

type MetaMapEntityExtractor 

type MetaMapEntityExtractor struct {
	// contains filtered or unexported fields
}

MetaMapEntityExtractor extracts CUI entities from queries.

func NewMetaMapEntityExtractor 

func NewMetaMapEntityExtractor(client metawrap.HTTPClient) MetaMapEntityExtractor

func (MetaMapEntityExtractor) Extract 

func (m MetaMapEntityExtractor) Extract(query cqr.CommonQueryRepresentation) (cqr.CommonQueryRepresentation, error)

type MetaMapKeywordMapper 

type MetaMapKeywordMapper struct {
	// contains filtered or unexported fields
}

MetaMapKeywordMapper uses MetaMap to map entities (CUIs) to keywords.

func NewMetaMapKeywordMapper 

func NewMetaMapKeywordMapper(client metawrap.HTTPClient, mapper MetaMapMapper) MetaMapKeywordMapper

NewMetaMapKeywordMapper creates a new keyword mapper that uses MetaMap.

func (MetaMapKeywordMapper) Map 

func (m MetaMapKeywordMapper) Map(keyword cqr.Keyword) (keywords []cqr.CommonQueryRepresentation, err error)

Map maps text to several concepts.

type MetaMapMapper 

type MetaMapMapper func(keyword cqr.Keyword) ([]cqr.CommonQueryRepresentation, error)

MetaMapMapper maps candidates from MetaMap to one or more keywords.

func Alias 

func Alias(mapping cui2vec.AliasMapping) MetaMapMapper

Frequent identifies all of the terms for the concept in the UMLS meta-thesaurus.

func ElasticUMLS 

func ElasticUMLS(c *elastic.Client) MetaMapMapper

func Frequent 

func Frequent(mapping cui2vec.Mapping) MetaMapMapper

Frequent identifies the most frequently used term for the concept in the UMLS meta-thesaurus.

func Matched 

func Matched() MetaMapMapper

Matched uses the Matched entity from MetaMap.

func MeSHMapper 

func MeSHMapper(mapper MetaMapMapper) MetaMapMapper

MeSHMapper uses the output of another MetaMap mapper to assign MeSH terms.

func Preferred 

func Preferred(client guru.UMLSClient) MetaMapMapper

Preferred uses the Preferred entity from UMLS.

type NLPLogicComposer 

type NLPLogicComposer struct {
	// contains filtered or unexported fields
}

NLPLogicComposer composes queries logically using the stanford English parser.

func NewNLPLogicComposer 

func NewNLPLogicComposer(javaClassPath string) *NLPLogicComposer

func (NLPLogicComposer) Compose 

func (n NLPLogicComposer) Compose(query pipeline.Query) (cqr.CommonQueryRepresentation, error)

type ObjectiveFormulator 

type ObjectiveFormulator struct {
	Folder, Pubdates, SemTypes, MetaMapURL string

	MeSHK      []int
	DevK, PopK []float64
	// contains filtered or unexported fields
}

ObjectiveFormulator formulates queries according to the objective approach. This implementation writes files to disk as a side effect swhich can be later be used for analysis.

func NewObjectiveFormulator 

func NewObjectiveFormulator(s stats.EntrezStatisticsSource, esClient *elastic.Client, qrels trecresults.QrelsFile, population BackgroundCollection, folder, pubdates, semTypes, metamapURL string, optimisation eval.Evaluator, options ...ObjectiveOption) *ObjectiveFormulator

func (ObjectiveFormulator) Derive 

func (o ObjectiveFormulator) Derive() (cqr.CommonQueryRepresentation, cqr.CommonQueryRepresentation, []guru.MedlineDocument, []guru.MedlineDocument, []guru.MedlineDocument, error)

func (ObjectiveFormulator) Formulate 

func (o ObjectiveFormulator) Formulate(query pipeline.Query) ([]cqr.CommonQueryRepresentation, []pipeline.SupplementalData, error)

Formulate returns two queries: one with MeSH terms and one without. It also returns the set of unseen documents for evaluation later.

func (ObjectiveFormulator) Method 

func (o ObjectiveFormulator) Method() string

func (ObjectiveFormulator) Topic 

func (o ObjectiveFormulator) Topic() string

type ObjectiveOption 

type ObjectiveOption func(o *ObjectiveFormulator)

func ObjectiveAnalyser 

func ObjectiveAnalyser(analyser TermAnalyser, name string) ObjectiveOption

func ObjectiveGrid 

func ObjectiveGrid(devK, popK []float64, meshK []int) ObjectiveOption

func ObjectiveMinDocs 

func ObjectiveMinDocs(docs int) ObjectiveOption

func ObjectiveOptimisation 

func ObjectiveOptimisation(optimisation eval.Evaluator) ObjectiveOption

func ObjectivePopulation 

func ObjectivePopulation(population BackgroundCollection) ObjectiveOption

func ObjectivePostProcessing 

func ObjectivePostProcessing(processes ...PostProcess) ObjectiveOption

func ObjectiveQrels 

func ObjectiveQrels(rels trecresults.QrelsFile) ObjectiveOption

func ObjectiveQuery 

func ObjectiveQuery(query pipeline.Query) ObjectiveOption

func ObjectiveSeed 

func ObjectiveSeed(seed int) ObjectiveOption

func ObjectiveSplitter 

func ObjectiveSplitter(spitter Splitter) ObjectiveOption

type PopulationSet 

type PopulationSet TermStatistics

func (PopulationSet) Size 

func (p PopulationSet) Size() (float64, error)

func (PopulationSet) Statistic 

func (p PopulationSet) Statistic(term string) (float64, error)

type PostProcess 

type PostProcess func(query cqr.CommonQueryRepresentation) (cqr.CommonQueryRepresentation, error)

PostProcess applies any post-formatting to a query.

func Stem 

func Stem(original cqr.CommonQueryRepresentation) PostProcess

Stem uses already stemmed terms from the original query to replace terms from the query that requires post-processing.

type PubMedSet 

type PubMedSet struct {
	// contains filtered or unexported fields
}

func NewPubMedSet 

func NewPubMedSet(e stats.EntrezStatisticsSource) PubMedSet

func (PubMedSet) Size 

func (p PubMedSet) Size() (float64, error)

func (PubMedSet) Statistic 

func (p PubMedSet) Statistic(term string) (float64, error)

type QueryCategory 

type QueryCategory int

type RAKELogicComposer 

type RAKELogicComposer struct {
	// contains filtered or unexported fields
}

func NewRAKELogicComposer 

func NewRAKELogicComposer(semtypes, metamap string, titles map[string]string, seedPMIDs trecresults.QrelsFile, esClient *elastic.Client, vecClient *cui2vec.VecClient) RAKELogicComposer

func (RAKELogicComposer) Compose 

func (r RAKELogicComposer) Compose(query pipeline.Query) (cqr.CommonQueryRepresentation, error)

type RandomSplitter 

type RandomSplitter int64

func (RandomSplitter) Split 

func (r RandomSplitter) Split(docs []guru.MedlineDocument) ([]guru.MedlineDocument, []guru.MedlineDocument, []guru.MedlineDocument)

splitTest creates three slices of documents: 2:4 development, 1:4 validation, 1:4 unseen.

type Splitter 

type Splitter interface {
	Split(docs []guru.MedlineDocument) ([]guru.MedlineDocument, []guru.MedlineDocument, []guru.MedlineDocument)
}

Splitter splits a test set into development, validation, and unseen.

type TermAnalyser 

type TermAnalyser func(docs []guru.MedlineDocument) (TermStatistics, error)

TermAnalyser records term/phrase statistics about a set of documents.

type TermStatistics 

type TermStatistics map[string]float64

func RAKEAnalyser 

func RAKEAnalyser(docs []guru.MedlineDocument) (TermStatistics, error)

func TermFrequencyAnalyser 

func TermFrequencyAnalyser(docs []guru.MedlineDocument) (TermStatistics, error)

TermFrequencyAnalyser computes the document frequency for the input documents.

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