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Building Customer-Targeted
Search with Fusion
Andrew Oliver
March 22, 2017
Based in San Francisco
Offices in Bangalore, Bangkok,
New York City, Raleigh, Munich
Over 300 customers across the
Fortune 1000
Fusion, a Solr-powered platform
for search-driven apps
Consulting and support for
organizations using Solr
Produces the world’s largest open
source user conference dedicated
to Lucene/Solr
Lucidworks is the primary sponsor of
the Apache Solr project
Employs over 40% of the active
committers on the Solr project
Contributes over 70% of Solr's
open source codebase
40%
70%
• Over 50 connectors to
integrate all your data
• Robust parsing framework
to seamlessly ingest all your
document types
• Point and click Indexing
configuration and iterative
simulation of results for full
control over your ETL process
• Your security model
enforced end-to-end from
ingest to search across your
different datasources
Experience

Management
Operational Simplicity
SECURITY BUILT-IN
Shards Shards
Apache Solr
Apache Zookeeper
ZK 1
Leader
Election
Load
Balancing
Shared Config
Management
Worker Worker
Apache Spark
Cluster
Manager
RESTAPI
Admin UI
Lucidworks
View
LOGS FILE WEB DATABASE CLOUD
HDFS(Optional)
Core Services
• • •
ETL and Query Pipelines
Recommenders/Signals
NLP
Machine Learning
Alerting and Messaging
Security
Connectors
Scheduling
Fusion Simplifies the Deployment
Core Services
• • •
NLP
Recommenders / Signals
Blob Storage
Pipelines
Scheduling
Alerting / Messaging
Connectors
RESTAPI
Admin UI
Lucidworks
View
LOGS FILE WEB DATABASE CLOUD
• Seamless integration of your
entire search & analytics
platform
• All capabilities exposed
through secured API's, so you
can use our UI or build your
own.
• End-to-end security policies
can be applied out of the box
to every aspect of your search
ecosystem.
• Distributed, fault-tolerant
scaling and supervision of
your entire search application
Conversational Search:
“The principle behind conversational search
is that a user can speak a sentence into a
device, and that device can respond with a
full sentence.” -Technopedia
A Pathway to Better
Search
•Better Query Parsers
•Similarity
•Collaborative Recommendations
•Personalization
Dismax / Extended Dismax
•Searches and scores multiple fields
•Scores aren’t simply added
Similarity / More Like This
• Fusion Pipeline Stage takes a document as an argument, returns like
documents
• BM25 Similarity
• https://en.wikipedia.org/wiki/Okapi_BM25
Collaborative Recommendations
• Boost results users commonly click on
• Based on “Signals” - built into Fusion
• https://www.youtube.com/watch?v=0AwLSdcrJSc&sns=tw -
Demonstrated in last Webinar
Recommendations
Personalization
•Signals on a more per-user basis
•Boost things that I click on often
•Boost results like the ones I’ve clicked on
•More on this next time!
Language
• Easier and more
accurate than Natural
Language
• Domain phrases PE
Ratio, Stock Price,
SKU
• Entities: GE, IBM, etc
Domain Specific Language
Spoken
Language
•Speech to text
•Text-to-speech
•Mainly the latter is just
UI.
• Donald Bot
• Alexa
• Deep Drumpf
Conversational
https://
www.messenger.com/t/
thedonaldbot/
• https://twitter.com/
deepdrumpf
• http://
karpathy.github.io/
2015/05/21/rnn-
effectiveness/
Alexa
Cortona
Assistant
Etc
•Speech to text
•Search Engine
•UI Answers
• Tagging
• Faceting
• Domain Language
(Finance)
Open Calais
Demo
• Speech to Text
enabled Search
• Plugged into Fusion
Query Pipeline
• https://lucidworks.com/
2016/10/13/lucidworks-
integrates-ibm-watson-
into-fusion-enterprise-
discovery-platform/
Watson
Demo
RTFMBot
•Based on Chatterbot
•NLTK
•Train on Slack
•Answer Questions
generally with Fusion
search results
RTFMBot
Questions?
Building Customer-Targeted Search: March 15 @ 11am PT
https://lucidworks.com/webinar/building-customer-targeted-search-with-fusion/
Upcoming Webinars:

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Webinar: Building Customer-Targeted Search with Fusion

  • 1. Building Customer-Targeted Search with Fusion Andrew Oliver March 22, 2017
  • 2.
  • 3. Based in San Francisco Offices in Bangalore, Bangkok, New York City, Raleigh, Munich Over 300 customers across the Fortune 1000 Fusion, a Solr-powered platform for search-driven apps Consulting and support for organizations using Solr Produces the world’s largest open source user conference dedicated to Lucene/Solr Lucidworks is the primary sponsor of the Apache Solr project Employs over 40% of the active committers on the Solr project Contributes over 70% of Solr's open source codebase 40% 70%
  • 4.
  • 5. • Over 50 connectors to integrate all your data • Robust parsing framework to seamlessly ingest all your document types • Point and click Indexing configuration and iterative simulation of results for full control over your ETL process • Your security model enforced end-to-end from ingest to search across your different datasources
  • 8. SECURITY BUILT-IN Shards Shards Apache Solr Apache Zookeeper ZK 1 Leader Election Load Balancing Shared Config Management Worker Worker Apache Spark Cluster Manager RESTAPI Admin UI Lucidworks View LOGS FILE WEB DATABASE CLOUD HDFS(Optional) Core Services • • • ETL and Query Pipelines Recommenders/Signals NLP Machine Learning Alerting and Messaging Security Connectors Scheduling Fusion Simplifies the Deployment
  • 9. Core Services • • • NLP Recommenders / Signals Blob Storage Pipelines Scheduling Alerting / Messaging Connectors RESTAPI Admin UI Lucidworks View LOGS FILE WEB DATABASE CLOUD • Seamless integration of your entire search & analytics platform • All capabilities exposed through secured API's, so you can use our UI or build your own. • End-to-end security policies can be applied out of the box to every aspect of your search ecosystem. • Distributed, fault-tolerant scaling and supervision of your entire search application
  • 10. Conversational Search: “The principle behind conversational search is that a user can speak a sentence into a device, and that device can respond with a full sentence.” -Technopedia
  • 11. A Pathway to Better Search •Better Query Parsers •Similarity •Collaborative Recommendations •Personalization
  • 12. Dismax / Extended Dismax •Searches and scores multiple fields •Scores aren’t simply added
  • 13. Similarity / More Like This • Fusion Pipeline Stage takes a document as an argument, returns like documents • BM25 Similarity • https://en.wikipedia.org/wiki/Okapi_BM25
  • 14. Collaborative Recommendations • Boost results users commonly click on • Based on “Signals” - built into Fusion • https://www.youtube.com/watch?v=0AwLSdcrJSc&sns=tw - Demonstrated in last Webinar
  • 16. Personalization •Signals on a more per-user basis •Boost things that I click on often •Boost results like the ones I’ve clicked on •More on this next time!
  • 18. • Easier and more accurate than Natural Language • Domain phrases PE Ratio, Stock Price, SKU • Entities: GE, IBM, etc Domain Specific Language
  • 20. • Donald Bot • Alexa • Deep Drumpf Conversational
  • 24. • Tagging • Faceting • Domain Language (Finance) Open Calais
  • 25. Demo
  • 26. • Speech to Text enabled Search • Plugged into Fusion Query Pipeline • https://lucidworks.com/ 2016/10/13/lucidworks- integrates-ibm-watson- into-fusion-enterprise- discovery-platform/ Watson
  • 27. Demo
  • 28. RTFMBot •Based on Chatterbot •NLTK •Train on Slack •Answer Questions generally with Fusion search results
  • 30. Questions? Building Customer-Targeted Search: March 15 @ 11am PT https://lucidworks.com/webinar/building-customer-targeted-search-with-fusion/ Upcoming Webinars: