advanced query parsing techniques

Advanced Relevancy Ranking

Paul NelsonChief Architect / Search Technologies

2Search Technologies Overview

• Formed June 2005• Over 100 employees and growing• Over 400 customers worldwide• Presence in US, Latin America, UK & Germany• Deep enterprise search expertise• Consistent revenue growth and profitability• Search Engine Independent

3Lucene Relevancy: Simple Operators

• term(A) TF(A) * IDF(A)• Implemented with DefaultSimilarity / TermQuery• TF(A) = sqrt(termInDocCount)• IDF(A) = log(totalDocsInCollection/(docsWithTermCount+1)) + 1.0

• and(A,B) A * B• Implemented with BooleanQuery()

• or(A, B) A + B• Implemented with BooleanQuery()

• max(A, B) max(A, B)• Implemented with DisjunctionMaxQuery()

3

4Simple Operators - Example

and

or max

george martha washington custis

0.10 0.20 0.60 0.90

0.1 + 0.2 = 0.30 max(0, 0.9) = 0.90

0.3 * 0.9 = 0.27

5Less Used Operators

• boost(f, A) (A * f)• Implemented with Query.setBoost(f)

• constant(f, A) if(A) then f else 0.0• Implemented with ConstantScoreQuery()

• boostPlus(A, B) if(A) then (A + B) else 0.0• Implemented with BooleanQuery()

• boostMul(f, A, B) if(B) then (A * f) else A• Implemented with BoostingQuery()

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6Problem: Need for More Flexibility

• Difficult / impossible to use all operators• Many not available in standard query parsers

• Complex expressions = string manipulation• This is messy

• Query construction is in the application layer• Your UI programmer is creating query expressions?• Seriously?

• Hard to create and use new operators• Requires modifying query parsers - yuck

6

7

Solr

Query Processing Language 7

UserInterface

QPLEngine Search

QPLScript

8Introducing: QPL

• Query Processing Language• Domain Specific Language for Constructing Queries• Built on Groovy• https://wiki.searchtechnologies.com/index.php/QPL_Home_Page

• Solr Plug-Ins• Query Parser• Search Component

• “The 4GL for Text Search Query Expressions”• Server-side Solr Access

• Cores, Analyzers, Embedded Search, Results XML

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9Solr Plug-Ins

10QPL Configuration – solrconfig.xml

<queryParser name="qpl"class="com.searchtechnologies.qpl.solr.QPLSolrQParserPlugin">

<str name="scriptFile">parser.qpl</str><str name="defaultField">text</str>

</queryParser>

<searchComponent name="qplSearchFirst"class="com.searchtechnologies.qpl.solr.QPLSearchComponent">

<str name="scriptFile">search.qpl</str><str name="defaultField">text</str><str name="isProcessScript">false</str>

</searchComponent>

Query Parser Configuration:

Search Component Configuration:

11QPL Example #1

myTerms = solr.tokenize(query);

phraseQ = phrase(myTerms);

andQ = and(myTerms);

return phraseQ^3.0 | andQ^2.0 | orQ;

Tokenize:

Phrase Query:

And Query:

Put It All Together:

orQ = (myTerms.size() <= 2) ? null : orMin( (myTerms.size()+1)/2, myTerms);

Or Query:

12Thesaurus Example #2

myTerms = solr.tokenize(query);

thes = Thesaurus.load("thesaurus.xml")

thesQ = thes.expand(0.8f,solr.tokenizer("text"), myTerms);

return and(thesQ);

Tokenize:

Load Thesaurus: (cached)

Thesaurus Expansion:

Put It All Together:Original Query: bathroom humor

[or(bathroom, loo^0.8, wc^0.8), or(humor, jokes^0.8)]

13More Operators

Boolean Query Parser:pQ = parseQuery("(george or martha) near/5 washington")

Relevancy Ranking Operators:q1 = boostPlus(query, optionalQ)q2 = boostMul(0.5, query, optionalQ)q3 = constant(0.5, query)

Composite Queries:compQ = and(compositeMax(

["title":1.5, "body":0.8],"george", "washington"))

14News Feed Use Case 14

Order Documents Date1 markets+terms Today2 markets Today3 terms Today4 companies Today5 markets+terms Yesterday6 markets Yesterday7 terms Yesterday8 companies Yesterday9 markets, companies older

15News Feed Use Case – Step 1

markets = split(solr.markets, "\\s*;\\s*")marketsQ = field("markets", or(markets));

terms = solr.tokenize(query);termsQ = field("body",

or(thesaurus.expand(0.9f, terms)))

compIds = split(solr.compIds, "\\s*;\\s*")compIdsQ = field("companyIds", or(compIds))

Segments:

Terms:

Companies:

16News Feed Use Case – Step 2

todayDate = sdf.format(c.getTime())todayQ = field("date_s",todayDate)

c.add(Calendar.DAY_OF_MONTH, -1)yesterdayDate = sdf.format(c.getTime())yesterdayQ = field("date_s",yesterdayDate)

Today:

Yesterday:

sdf = new SimpleDateFormat("yyyy-MM-dd")cal = Calendar.getInstance()

17News Feed Use Case 17

Order Documents Date1 markets+terms Today2 markets Today3 terms Today4 companies Today5 markets+terms Yesterday6 markets Yesterday7 terms Yesterday8 companies Yesterday9 markets, companies older

18News Feed Use Case – Step 3

sq1 = constant(4.0, and(marketsQ, termsQ))sq2 = constant(3.0, marketsQ)sq3 = constant(2.0, termsQ)sq4 = constant(1.0, compIdsQ)subjectQ = max(sq1, sq2, sq3, sq4)

tq1 = constant(10.0, todayQ)tq2 = constant(1.0, yesterdayQ)timeQ = max(tq1, tq2)

recentQ = and(subjectQ, timeQ)

Weighted Subject Queries:

Weighted Time Queries:

Put it All Together:

return max(recentQ, or(marketsQ,compIdsQ)^0.01))

19Embedded Search Example #1

results = solr.search('subjectsCore', or(qTerms), 50)

subjectsQ = or(results*.subjectId)

return field("title", and(qTerms)) | subjectsQ^0.9;

Execute an Embedded Search:

Create a query from the results:

Put it all together:

qTerms = solr.tokenize(qTerms);

20Embedded Search Example #2

results = solr.search('categories', and(qTerms), 10)

myList = solr.newList();myList.add("relatedCategories", results*.title);

solr.addResponse(myList)

Execute an Embedded Search:

Create a Solr named list:

Add it to the XML response:

qTerms = solr.tokenize(qTerms);

21Other Features

• Embedded Grouping Queries• Oh yes they did!

• Proximity operators• ADJ, NEAR/#, BEFORE/#

• Reverse Lemmatizer• Prefers exact matches over variants

• Transformer• Applies transformations recursively to query trees

21

22

Solr

Query Processing Language 22

UserInterface

QPLEngine Search

Data as entered by user Boolean

Query ExpressionQPL

Script

ApplicationDev Team

Search Team

23

Solr

QPL: Using External Sources to Build Queries 23

UserInterface

QPLEngine Search

QPLScript

RDBMS OtherIndexes Thesaurus

CONTACT

Paul Nelsonpnelson@searchtechnologies.com