your own recommendation engine with neo4j and reco4php - dpc16

YourownRecommendation

EnginewithNeo4j andReco4PHP

Aboutme

• ChristopheWillemsen

• Neo4j&Elasticsearch Consultant@GraphAware

• Belgium

@ikwattro

Whatwe’lltalkabout

• Challengesofarecommendationengine

• Quickintrotographdatabases(Neo4j)

• Reco4PHP

• Buildyourown(demo)

Challengesofa

RecommendationEngine

Recommendations:Overview

• Newsyoushouldread(blogs)• Booksyoushouldbuy(e-commerce)• Personsyoumayknow(social)• Whichtalktoattend(knowledge)• Whichserviceisbestsuitedtohandleagivenfailure(impactanalysis)• Findingtherightcandidatesformedicalproofs(healthcare)• …

Maintypesofrecommendations

• Contentbased(features)• Collaborativefiltering(relationsuser<->item,knn,matrixfactorization)• Knowledgebased

Combinationofthosebycompletelycrazyscientists+secretsauce

BusinessChallenges

• Findingthingstorecommend

• Servethemostrelevantrecommendations

•Measuringthequalityofrecommendations

• Timetomarket/costofdevelopment

Businesschallenges

Imaginethatyoushouldimplementthefeature

“Peopleyoumayknow”onLinkedIn

Businesschallenges:Findingcandidates• Commoncontacts• Facebookfriendsincommon•Mobile/emailcontactsincommon• Allcontactsofyourcontacts•Workedforsamecompany• Studiedatsameschool• Sharesameinterests• Livesinsamecity

Businesschallenges

It’sjustthebeginning!

Let’srevisit…

Businesschallenges:mostrelevant

Morecontactsincommon:

Morerelevant?

Businesschallenges:mostrelevant

Samecity,workedforsamecompany,studiedatsameschool

Businesschallenges:mostrelevant

Whattodowithemailsthatactuallydon’trepresentaperson?

Shouldwerecommend info@coolblue.nl?

Businesschallenges:mostrelevant

Whatshouldwedowithcontacts

pending?rejected?

alwaysignored?

TechnicalChallenges

• Simplicity

• Performance(Real-timeornearreal-time)

• Flexibility

IntrotoGraphDatabases

(Neo4j)

isagraphdatabase.

Nodes

Anodecanhaveoneormultiplelabels

Person, Male

Anodecanoneormoreproperties

Person, Male

name : Mark

Nodesareconnectedbyrelationships

Relationshipshaveatype

Relationshipshaveadirection

Relationshipscanhaveproperties

Cypher:thequerylanguageforgraphs

Declarativepatternmatchinglanguage

Describewhatyouwant

toretrievefromthedatabase,not

howtogetit.

Declarativepatternmatchinglanguage

MATCH(you:Person {name:”You”})-[:ATTENDED]->(talk),

(talk)<-[:ATTENDED]-(other)

WHERE(you)-[:LIVES_IN]->(city)<-[:LIVES_IN]-(other)

ANDyou <>other

RETURNother ASmaybeFriend

Whygraphs?

TechnicalChallenges

• Simplicity

• Performance(Real-timeornearreal-time)

• Flexibility

Simplicity

Features aswellasrelationships arenaturallyrepresentedin

agraph database.

Simplicity

Therecommendation logiccanberepresentedinagraphtraversal.

TechnicalChallenges

• Simplicity

• Performance(Real-time)

• Flexibility

Performance

• Relationshipsarefirstclasscitizens(nojoins!)• TraversingrelationshipsinNeo4jischeap(4millionstraversalspersecondpercore)

Reco4PHP

OpenSourceRecommendationEngine

SkeletonatopNeo4j

Reco4PHP

• StandalonePHPlibrary• Opinionatedarchitecture• Flexible• Handlealltheglue

Architecture

• Input->DiscoveryEngines->Recommendations• ScoresandScorebuilders• BlacklistsandFilters• PostProcessors• Context(howmany,meteo,allk/vexternalfactors..)

Designdecisions

• DiscoveryEngine perrecommendation“reason”(corelogic)• DiscoveryEngine executesagraphtraversal(Cypherquery)• Itemsdiscoveredmultipletimesaremorerelevant

TechnicalChallenges

• Simplicity

• Performance(Real-timeornearreal-time)

• Flexibility

Let’sbuildone

In5minutes,we’llbuildasimpleenginethatrecommendsrepositoriesyoumightbeinterestedinonGithub.

composerrequiregraphaware/reco4php

0.TheModel

:STARS

:CONTRIBUTED_TO:OWNS

:FOLLO

WS:FOLLOWS

:WRITTEN_IN

1.Discover

Findrepositoriesstarredbythepeopleyoufolloworfollowingyou.

2.Serveonlyrelevantrecommendations

We’llcreateablacklistthatwillexcludetherepositoriesIamtheownerof.

3.Postprocess

We’llrewardtherecommendedrepositoriesbylet’ssay5pointsiftheyarewritteninPHP.

4.Assemble

5.Tadaaaaaam

Thankyou!

Questions?

graphaware.comgithub.com/graphaware

@ikwattro