A talk on Faceted Search And Result Reordering

1. Faceted Search
And Result
Reordering
Varun Thacker, Unbxd Inc.

2. Agenda
● Facets
○ Introduction
○ Multi Select Faceting
○ Dynamic Range Faceting
● Reordering Documents
○ Default Scoring Formula
○ Function Queries To Reorder Documents
○ Query Elevation Component
● Query Elevation Component

3. Faceted Search
● Also known as guided navigation
● Essentially it's a group by on a field
● Values returned are calculated on the
documents from the search results

4. Brand Facet
Price Facet
Counts
Total Count

5. How can we this
Implement In Solr
● q = android phones
● facet = true
● facet.field = brand
● facet.range = price
● facet.range.start=0
● facet.range.end=1000
● facet.range.gap=100
● To Filter Results: &fq=brand:"HTC"

6. Response in XML
<lst name="facet_counts">
<lst name="facet_queries"/>
<lst name="facet_fields">
<lst name="brand">
<int name="Samsung">293</int> <int name="HTC">100</int> ...
</lst>
</lst>
<lst name="facet_dates"/>
<lst name="facet_ranges">
<lst name="price">
<lst name="counts">
<int name="0">0</int> <int name="100">11</int> ...
</lst>
<int name="gap">100</int>
<int name="start">0</int>
<int name="end">500</int>
</lst>
</lst>
</lst>

7. Dynamic Price
Range
Total Count
Filters Applied
Filter + Dynamic Price Range

8. Implementing Dynamic
Price Range
Dynamic range faceting means that we can
group results into buckets of sizes that you
want instead of a fixed bucket range and gap
● &q = *
● &facet = true
● &facet.field = Brand
● &facet.query = Price:[0 TO 5000]
● &facet.query = Price:[5001 TO 8000]
● &facet.query = Price:[8001 TO 15000]
● &facet.query = Price:[15001 TO *]

9. Multi-Select Faceting
Example
Multi-Select Faceting gives the ability
to display facet counts despite the
result set being filtered
Multi-Select
Faceting
gives the
ability to
display facet
counts of
other brands
despite the
result set
being filtered
on brand HTC

10. Multi-Select Faceting
Implementation
● tag: Tags a filter with an arbitrary name
● ex: Excludes a tag filter from being applied on a
facet field/query.
● key: Tags a facet field an arbitrary name (instead
of field name).
To Implement In Solr:
● q = android phones
● facet = true
● fq = {!tag=brand_tag}brand:"HTC"
● facet.field = {!ex=brand_tag}brand

11. Result Options
● Sort by relevancy
○ Default TF-IDF Scores
○ Boost cheaper products
○ Boost newer products
○ Boost high average user clicks and user ratings
○ Boost high selling products
● Fix top results on a per query basis

12. Function Queries
● Apply functions to a field to alter the score of
a document
● It iterates over all documents serially
applying the function
● Can be multiplied into the score by using the
boost param in the eDismax request handler

13. TF-IDF Scoring
● tf - Number of times a term occurs in a
document
● idf - Measure of how unique a term is
● lengthNorm - Penalizes long docs with few
term occurrences on index time.
● Doesn't work well for small documents

14. Boost cheaper products
● Blindly sort the result
○ &sort = price asc
● Give preference to cheaper products
○ Boost value of 2 for the cheapest product
○ Boost value of 1 for the most expensive product
○ &bf = add(div(sub(price, min), sub(max, min)), 1)
■ Use the StatsComponent to get min,max
■ Use the min, max function queries
■ Know your data and use realistic values

15. Boosting Newer Products
● Blindly sort the result
○ &sort = release_date desc
● Give preference to Newer Products
○ recip(ms(NOW/DAY,pub_date),3.16e-11,1,1)
○ Where recip(m, x, a, b) = a / (mx + b)
○ Picking a=2, b =1, m = 3.16e-11
○ Gives a boost =2 for todays product
○ Gives a boost =1.3 for 1/2 year old product
○ Gives a boost =1 for 1 year old product and so on

16. Boost high margin
products
● You have a index field called margin
● Again you can always sort on this field
● Or you can give it subtle boosts
○ Let's say you want to boost product which have a
margin more than 50%
○ map(margin_field, 50, 100, 2)
● You can use a high selling, user rating
approach instead too

17. Query Elevation
Component
● Fix particular documents for certain queries
● No scoring is taken into consideration for
these queries
<elevate>
<query text="android phones">
<doc id="nexus 4" />
<doc id="pick a phone :)" exclude="true"/>
</query>
</elevate>

18. Conclusion
● Facets have a lot of other use cases -
Analytics. Ex. Range facets to populate
histograms
● Always keep tweaking parameters and
measuring effectiveness of your function
queries.
● Use Query Elevation Component for your
top queries

19. Thank You
Questions?