How to use click data to: 1) improve relevance calculations 2) improve recall by extending returns 3) customise, personalise & diversify returns 4) exploit collective knowledge and make recommendations 5) respond, adapt & evolve Overall, a form of self-organising “Knowledge Map”, built and applied from the bottom up. Click data enables simple, flexible, scalable methods that can run at query time. Using click data to adjust query returns results in an ongoing implicit feedback process and easy significant improvements. This requires no models, external data, large sparse matrices, clustering, machine learning etc., and helps deal with many of the usual problems associated with collaborative methods. For further detail see http://www.slideshare.net/pontneo/better-search-implementation-of-click-through-filter-as-a-query-parser-plugin-for-apache-solr-lucene

1. 5 useful things to do
with click data
Dr. Gavin Ruddy
gav@pontneo.com
12 Oct 2015

2. 1: improve relevance
match with
high click rate
match with
low click rate
boost useful itemsquery
lots of items
clicking provides direct user feedback

3. 2: broaden responses
query
intersecting
clickstream
data
extended return
click traffic identifies important connections

4. 3: refine point of view
query focussed return
e.g. filter
by user
type
different groups can see things differently

5. 4: knowledge sharing
e.g. things I visit things I might like
click data reflects collective understanding

6. 5: implicit adaptation
query dynamic return
new
clicking
change
natural change via an implicit feedback loop

7. … overall …
lots of items
click data enables
a self-organising
“Knowledge Map”,
built and applied
from the bottom up

8. … so what …
• continual intelligent filtering
• flexible, scalable methods that run at query time
• does not require complex models, data or techniques
• significant, low risk improvements
• useful in many situations
• effectively controlled by how you choose to integrate
click data over time
• helps deal with many of the usual problems
associated with collaborative methods

9. … but it’s complicated …
• no it isn’t
• click signal can be noisy, but there’s lots of it,
it’s all real and it’s highly dynamic
• just record appropriate clicks in a useful form for
integration into your queries (e.g. fromID, toID
pairs with a timestamp)
• for more detail on how to go about applying
these methods, see “Click-Through Filter” e.g.
http://www.slideshare.net/pontneo/better-search-implementation-
of-click-through-filter-as-a-query-parser-plugin-for-apache-solr-
lucene

10. … but it’s complicated …
• no it isn’t
• click signal can be noisy, but there’s lots of it,
it’s all real and it’s highly dynamic
• just record appropriate clicks in a useful form for
integration into your queries (e.g. fromID, toID
pairs with a timestamp)
• for more detail on how to go about applying
these methods, see “Click-Through Filter” e.g.
http://www.slideshare.net/pontneo/better-search-implementation-
of-click-through-filter-as-a-query-parser-plugin-for-apache-solr-
lucene