It's Just Search: Presented by Erik Hatcher, Lucidworks

•

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Erik Hatcher presented on various techniques for enhancing search experiences, including: - Using rules, signals, and location awareness to incorporate additional context into search results. - Combining techniques like typeahead, autocomplete, suggestion, and instant search. - Leveraging features such as relevancy ranking, faceting, highlighting, and result grouping. - Integrating these "just search" techniques can create synergy and emergent behaviors that improve the overall search experience.

Technology

O C T O B E R 1 1 - 1 4 , 2 0 1 6 • B O S T O N , M A

It’s Just Search
Erik Hatcher
Co-founder and Senior Solutions Architect, Lucidworks

Think inside the box. Inside the search box, that is.
The "best"* search results incorporate many more factors than (just) textual matching
and relevancy. Search experience owners manage query context rules, signals
automatically feed back machine learned factors, users implicit and explicit behaviors
ﬁlter and weight future interactions. Synergy emerges with several cooperating (just)
searches.
This talk will showcase and detail several (just) search examples including rules,
typeahead/suggest, signals, and location awareness, bringing them all together into a
cohesive search experience.
Abstract

• Lucene/Solr Committer
• Apache Software Foundation Member
• Creator of Blacklight
• Co-author of “Ant in Action” and “Lucene in Action”
• Co-founder and Senior Solutions Architect at Lucidworks
About me
@erikhatcher

Anatomy of Search Results
Relevancy ranked results

• relevancy ranked results
• faceting
• highlighting
• grouping (collapsing)
• more-like-this
• did-you-mean (spellcheck)
Search Features

typeahead,  
autocomplete,  
suggest,  
instant search

• query a “typed” n-grammed index, and get “typed” results
• type examples: brands, categories, specialties,
treatments, providers/doctors, products
• suggest Things Not Strings
• things have attributes: metadata
(known) entity detection

• /select?q=sea…
• q=<what user typed>
• Response includes grouped and ranked results,
highlighting, and spellcheck suggestions
typeahead request

• clicks and queries
• add-to-carts
• user history, behavior, and preferences
• geo-location, device
signals and recommendations

$• <collection>/select?q=search • <collection>_signals_aggr/select • ?q=${q} • qf, pf, sort • ==> bq: "id:7^1.0" signals sub-query$

• trigger off query context
• query, ﬁlters, date/time, tags
• actions -
• boost, block, banner, redirect, set parameters,  
rewrite query, etc
• superset of signals
• signals: automated feedback
• rules: manually created
rules

$• <collection>/select?q=solr search  [&tags=mobile,production] • <collection>_rules/select • ?q=${q} • &fq=-enabled:false • &fq=…effective_range:$now… • &fq=…tags:($tags)… • process rules returned • manipulate request, append to response rules sub-query$

$• /providers/select?q=jones&zipcode=10301 • /zipcodes/select?q={!term f=zipcode_s v=$zipcode} zipcodes collection zipcodes.csv ZipCode,State,City,County,Latitude,Longitude,AreaCode,TimeZone,DST 85701,AZ,Tucson,Pima,32.216091,-110.97099,520,-7,N 10301,NY,Staten Island,Richmond,40.6226,-74.0992,718,-5,Y 22901,VA,Charlottesville,Albemarle,38.071751,-78.503937,434,-5,Y, fl += dist:geodist() fq += {!geofilt} pt = ${zipcode_doc.latlon_srpt} sfield = locations_rpt d = 10 sort = geodist() asc$

•simple things working
together
•whole is greater than
the sum of the parts
•feedback loops
•emergent behavior
Synergy

• Presentation materials:
• https://github.com/erikhatcher/searchcamp
• Search Hub:
• http://searchhub.lucidworks.com/
• Fusion (platform used for presentation):
• https://lucidworks.com/products/fusion/
See Also
@erikhatcher

Lucidworks Fusion Is Search-Driven Everything
Access data from
anywhere to build
intelligent, data-
driven applications.
Data Acquisition
Indexing & Streaming
Smart Access API
Recommendations & 
Alerts
Analytics & InsightsExtreme Relevancy
CUSTOMER
SERVICE
RESEARCH
PORTAL
DIGITAL
CONTENT
CUSTOMER
INSIGHTS
FRAUD
SURVEILLANCE
ONLINE 
RETAIL

• https://commons.wikimedia.org/wiki/File:Ant_bridge.jpg 
• http://jillian.rootaction.net/?p=340 
• https://commons.wikimedia.org/wiki/
File:Turtles.on.a.stone.in.brazil.jpg
image credits

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Information architecture (IA) involves organizing and labeling information to support findability and usability. Core IA techniques include card sorting to group content and category testing to validate information structures. IA is an iterative process that fits within user-centered design and involves user research, prototyping, and evaluation. Effective IA supports different search behaviors through clear labeling, multiple access paths, and appropriate structures that match user mental models.

Reflected intelligence evolving self-learning data systems

Trey Grainger

In this presentation, we’ll talk about evolving self-learning search and recommendation systems which are able to accept user queries, deliver relevance-ranked results, and iteratively learn from the users’ subsequent interactions to continually deliver a more relevant experience. Such a self-learning system leverages reflected intelligence to consistently improve its understanding of the content (documents and queries), the context of specific users, and the collective feedback from all prior user interactions with the system. Through iterative feedback loops, such a system can leverage user interactions to learn the meaning of important phrases and topics within a domain, identify alternate spellings and disambiguate multiple meanings of those phrases, learn the conceptual relationships between phrases, and even learn the relative importance of features to automatically optimize its own ranking algorithms on a per-query, per-category, or per-user/group basis.

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This document discusses a partnership between IBM Commerce and Lucidworks to improve e-commerce search experiences. Key points: 1. The partnership will integrate Lucidworks' Apache Solr-based search platform Fusion with IBM Commerce to power search and recommendations on IBM Commerce sites. 2. Fusion will enrich product content, queries, and results to improve findability. It will also use signals from user interactions for more relevant results and personalized recommendations. 3. The integration aims to improve customer experiences and conversions by ensuring customers can find products through various query types and discover related items to buy.

Lab EPiServer Find - Advanced developer scenarios

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The document provides an overview of EPiServer Find, an advanced search engine for EPiServer. It discusses unified search capabilities including searching across different content types and customizing projections. It also covers highlighting search results, usage statistics and tracking, and demo functionality like autocomplete, spellchecking, and did you mean suggestions. The presentation includes demos of filtering, facets, and multi-search queries. Lab exercises are proposed to practice common search scenarios using the EPiServer Find API.

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Comperio - Search Matters.

This document discusses search analytics and best practices for improving search experiences. It begins by distinguishing between web analytics, which shows what users do, and search analytics, which shows their intent. The document then outlines various challenges with search like inability to find information, outdated content, and poor user experience. It recommends monitoring search logs to understand frequent and unique queries as well as those with no results. The rest of the document provides tips for tuning relevancy, defining search goals and scope, applying filters and boosts, and establishing a search team for ongoing maintenance. It emphasizes the importance of search analytics for understanding users and improving search quality.

Thought Vectors and Knowledge Graphs in AI-powered Search

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While traditional keyword search is still useful, pure text-based keyword matching is quickly becoming obsolete; today, it is a necessary but not sufficient tool for delivering relevant results and intelligent search experiences. In this talk, we'll cover some of the emerging trends in AI-powered search, including the use of thought vectors (multi-level vector embeddings) and semantic knowledge graphs to contextually interpret and conceptualize queries. We'll walk through some live query interpretation demos to demonstrate the power that can be delivered through these semantic search techniques leveraging auto-generated knowledge graphs learned from your content and user interactions.

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Semtech bizsemanticsearchtutorial

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The document discusses the evolution of search engines from basic keyword search to semantic search using knowledge graphs and structured data. It provides examples of how search engines like Google are now able to provide direct answers to queries by searching structured data rather than just documents. It emphasizes the importance of representing web content as structured data using schemas like schema.org to be discoverable in semantic search and knowledge graphs.

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Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.

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This document introduces Texifter tools and methods for analyzing large amounts of structured and unstructured text. [1] The tools help users discover information to streamline processes, increase ROI, and identify trends. [2] The main tool is DiscoverText, a cloud-based platform that moves users from data to insights through human and machine collaboration. [3] The tools help analysts better organize, access, and extract valid insights from data through a combination of human judgment and computer algorithms.

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The document discusses various approaches to AI-powered search, including content understanding through keyword search, user understanding through collaborative recommendations, and combining the two through personalized search. It then covers domain understanding using knowledge graphs, combining domain and user understanding through domain-aware matching, and combining content and domain understanding through semantic search. Finally, it discusses balancing keyword, vector, and knowledge graph search approaches.

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With ecommerce experiencing explosive growth, it seems intuitive that the B2B segment of that ecosystem is mirroring the same trajectory. That said, B2B has very different needs when it comes to transacting with the same style of experiences that we see in B2C. For instance, B2B ecommerce is about precision findability, whereas B2C customers can convert at higher rates when they’re just browsing online. In order for the B2B buying experience to be successful, search needs to be tuned to meet the unique needs of the segment. In this webinar with Forrester senior analyst Joe Cicman, you’ll learn: -Which verticals in B2B will drive the most growth, and how machine-learning powered personalization tactics can be deployed to support those specific verticals -Why an omnichannel selling approach must be deployed in order to see success in B2B -How deploying content search capabilities will support a longer sales cycle at scale -What the next steps are to support a robust B2B commerce strategy supported by new technology Speakers Joe Cicman, Senior Analyst, Forrester Jenny Gomez, VP of Marketing, Lucidworks

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Customer loyalty starts with quickly responding to your customer’s needs. When it comes to resolving open support cases, time is of the essence. Time spent searching for answers adds up and creates inefficiencies in resolving cases at scale. Relevant answers need to be a few clicks away and easily accessible for agents directly from their service console. We will explore how Lucidworks’ Agent Insights application automatically connects agents with the correct answers and resources. You’ll learn how to: -Configure a proactive widget in an agent’s case view page to access resources across third-party systems (such as Sharepoint, Confluence, JIRA, Zendesk, and ServiceNow). -Easily set up query pipelines to autonomously route assets and resources that are relevant to the case-at-hand—directly to the right agent. -Identify subject matter experts within your support data and access tribal knowledge with lightning-fast speed.

How Crate & Barrel Connects Shoppers with Relevant Products

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Lunch and Learn during Retail TouchPoints #RIC21 virtual event. *** Crate & Barrel’s previous search solution couldn’t provide its shoppers with an online search and browse experience consistent with the customer-centric Crate & Barrel brand. Meanwhile, Crate & Barrel merchandisers spent the bulk of their time manually creating and maintaining search rules. The search experience impacted customer retention, loyalty, and revenue growth. Join this lunch & learn for an interactive chat on how Crate & Barrel partnered with Lucidworks to: -Improve search and browse by modernizing the technology stack with ML-based personalization and merchandising solutions -Enhance the experience for both shoppers and merchandisers -Explore signals to transform the omnichannel shopping experience Questions? Visit https://lucidworks.com/contact/

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Learn how to guide customers to relevant products using eCommerce search, hyper-personalisation, and recommendations in our ‘Best-In-Class Retail Product Discovery’ webinar. Nowadays, shoppers want their online experience to be engaging, inspirational and fulfilling. They want to find what they’re looking for quickly and easily. If the sought after item isn’t available, they want the next best product or content surfaced to them. They want a website to understand their goals as though they were talking to a sales assistant in person, in-store. In this webinar, we explore IMRG industry data insights and a best-in-class example of retail product discovery. You’ll learn: - How AI can drive increased revenue through hyper-personalised experiences - How user intent can be easily understood and results displayed immediately - How merchandisers can be empowered to curate results and product placement – all without having to rely on IT. Presented by: Dave Hawkins, Principal Sales Engineer - Lucidworks Matthew Walsh, Director of Data & Retail - IMRG

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Many companies claim personalization and omnichannel capabilities are top priorities. Few are able to deliver on those experiences. For a recent Lucidworks-commissioned study, Forrester Consulting surveyed 350+ global business decision-makers to see what gets in the way of achieving these goals. They discovered that inefficient technology, lack of behavioral insights, and failure to tie initiatives to enterprise-wide goals are some of the most frequent blockers to personalization success. Join guest speaker, Forrester VP and Principal Analyst, Brendan Witcher, and Lucidworks CEO, Will Hayes, to hear the results of the Forrester Consulting study, how to avoid “digital blindness,” and how to apply VoC data in real-time to delight customers with personalized experiences connected across every touchpoint. In this webinar, you’ll learn: - Why companies who utilize real-time customer signals report more effective personalization - How to connect employees and customers in a shared experience through search and browse - How Lucidworks clients Lenovo, Morgan Stanley and Red Hat fast-tracked improvements in conversion, engagement and customer satisfaction Featuring - Will Hayes, CEO, Lucidworks - Brendan Witcher, VP, Principal Analyst, Forrester

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Intelligent Policing. Leveraging Data to more effectively Serve Communities. Policing in the next decade is anticipated to be very different from historical methods. More data driven, more focused on the intricacies of communities they serve and more open and collaborative to make informed recommendations a reality. Whether its social populations, NIBRS or organization improvement that’s the driver, the IT requirement is largely the same. Provide 360 access to large volumes of siloed data to gain a full 360 understanding of existing connections and patterns for improved insight and recommendation. Join us for a round table discussion of how the Toronto Police Service is better serving their community through deploying a unified intelligent data platform. Data innovation improves officers' engagement with existing data and streamlines investigation workflows by enhancing collaboration. This improved visibility into existing police data allows for a more intelligent and responsive police force. In this webinar, we'll cover: -The technology needs of an intelligent police force. -How a Global Search improves an officer's interaction with existing data. Featuring: -Simon Taylor, VP, Worldwide Channels & Alliances, Lucidworks -Michael Cizmar, Managing Director, MC+A -Ian Williams, Manager of Analytics & Innovation, Toronto Police Service

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Policing in the next decade is anticipated to be very different from historical methods. More data driven, more focused on the intricacies of communities they serve and more open and collaborative to make informed recommendations a reality. Whether its social populations, NIBRS or organization improvement that’s the driver, the IT requirement is largely the same. Provide 360 access to large volumes of siloed data to gain a full 360 understanding of existing connections and patterns for improved insight and recommendation. Join us for a round table discussion of how the Toronto Police Service is better serving their community through deploying a unified intelligent data platform. Data innovation improves officers' engagement with existing data and streamlines investigation workflows by enhancing collaboration. This improved visibility into existing police data allows for a more intelligent and responsive police force. In this webinar, we'll cover: The technology needs of an intelligent police force. How a Global Search improves an officer's interaction with existing data. Featuring -Simon Taylor, VP, Worldwide Channels & Alliances, Lucidworks -Michael Cizmar, Managing Director, MC+A -Ian Williams, Manager of Analytics & Innovation, Toronto Police Service

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This document provides a framework for prioritizing onsite search problems and key performance indicators (KPIs) to measure for e-commerce search optimization. It recommends prioritizing fixing searches that yield no results, improving relevance of results, and reducing false positives. The most essential KPIs to measure include query latency, throughput, result relevance through click-through rates and NDCG scores. The document also provides tips for self-benchmarking search performance and examples of search performance benchmarks across nine e-commerce sites from various industries.

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Wish your conversion rates were higher? Can’t figure out how to efficiently and effectively serve all the visitors on your site? Embarrassed by the quality of your product discovery experience? The bar is high and the influx of online shopping over recent months has reminded us that the opportunities are real. We’re all deep in holiday prep, but let’s take a few minutes to think about January 2021 and beyond. How can we position ourselves for success with our customers and against our competition? Grab your lunch and let’s dive into three strategies that need to be part of your 2021 roadmap. You don’t need an army to get there. But you do need to take action and capitalize on the shoppers abandoning the product discovery journey on your site. In this session, attendees will find out how to: -Take control of merchandising at scale; -Implement hands-free search relevancy; and -Address personalization challenges.

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For a personalized search experience, search curation requires robust text interpretation, data enrichment, relevancy tuning and recommendations. In order to achieve this, language and entity identification are crucial. For teams working on search applications, advanced language packages allow them to achieve greater recall without sacrificing precision. Join us for a guided tour of our new Advanced Linguistics packages, available in Fusion, thanks to the technology partnership between Lucidworks and Basistech. We’ll explore the application of language identification and entity extraction in the context of search, along with practical examples of personalizing search and enhancing entity extraction. In this webinar, we’ll cover: -How Fusion uses the Rosette Basic Linguistics and Entity Extraction packages -Tips for improving language identification and treatment as well as data enrichment for personalization -Speech2 demo modeling Active Recommendation -Use Rosette’s packages with Fusion Pipelines to build custom entities for specific domain use cases Featuring: -Radu Miclaus, Director of Product, AI and Cloud, Lucidworks, Lucidworks -Robert Lucarini, Senior Software Engineer, Lucidworks -Nick Belanger, Solutions Engineer, Basis Technology

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Before COVID-19, almost 80% of the US workforce worked service in jobs that involve in-person interaction with strangers. Now, leaders of service organizations must reshape their offerings during the pandemic and prepare for whatever the new normal turns out to be. Our three panelists will share ideas for adapting their service businesses, now that closer-than-six-feet isn’t an option. Join Lucidworks as we talk shop with 3 service business leaders, covering: -Common impacts of the pandemic on service businesses (and what to do about them), -How service teams can maintain a human touch across virtual channels, and -Plans for the future, before and after the pandemic subsides. Featuring -Sara Nathan, President & CEO, AMIGOS -Anthony Carruesco, Founder, AC Fly Fishing -sara bradley, chef and proprietor, freight house -Justin Sears, VP Product Marketing, Lucidworks

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The COVID-19 pandemic has forced companies to support far more customers and employees through digital channels than ever before. Many are turning to chatbots to help meet increasing demand, but traditional rules-based approaches can’t keep up. Our new Smart Answers add-on to Lucidworks Fusion makes existing chatbots and virtual assistants more intelligent and more valuable to the people you serve.

Smart Answers for Employee and Customer Support After COVID-19

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Watch our on-demand webinar showcasing Smart Answers on Lucidworks Fusion. This technology makes existing chatbots and virtual assistants more intelligent and more valuable to the people you serve. In this webinar, we’ll cover off: -How search and deep learning extend conversational frameworks for improved experiences -How Smart Answers improves customer care, call deflection, and employee self-service -A live demo of Smart Answers for multi-channel self-service support

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In the current climate, it’s now more important than ever to digitally enable your workforce and customers. Hear from Simon Taylor, VP Global Partners & Alliances, Lucidworks and Matt Aslett, Research Vice President, 451 Research to get the inside scoop on how industry leaders in Europe are developing and executing their digital transformation strategies. In this webinar, we’ll discuss: The top challenges and aspirations European business and technology leaders are solving using AI and search technology Which search and AI use cases are making the biggest impact in industries such as finance, healthcare, retail and energy in Europe What technology buyers should look for when evaluating AI and search solutions

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This document introduces Fusion 5.1 and its new capabilities for integrating with data science tools like Tensorflow, Scikit-Learn, and Spacy. It provides an overview of Fusion's capabilities for understanding content, users, and delivering insights at scale. The document then demonstrates Fusion's Jupyter Notebook integration for reading and writing data and running SQL queries. Finally, it shows how Fusion integrates with Seldon Core to easily deploy machine learning models with tools like Tensorflow and Scikit-Learn. A live demo is provided of deploying a custom model and using it in Fusion's query and indexing pipelines.

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In this webinar with 451 Research, you'll understand how retailers are using AI to predict customer intent and learn which key performance metrics are used by more than 120 online retailers in Lucidworks’ 2019 Retail Benchmark Survey. In this webinar, you’ll learn: ● What trends and opportunities are facing the ecommerce industry in 2020 ● Why search is the universal path to understanding customer intent ● How large online retailers apply AI to maximize the effectiveness of their personalization efforts

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Nordstrom Rack | Hautelook curates and serves customers a wide selection of on-trend apparel, accessories, and shoes at an everyday savings of up to 75 percent off regular prices. With over a million visitors shopping across different platforms every day, and a realization that customers have become accustomed to robust and personalized search interactions, Nordstrom Rack | Hautelook launched an initiative over a year ago to provide data science-driven digital experiences to their customers. In this session, we’ll discuss Nordstrom Rack | Hautelook’s journey of operationalizing a hefty strategy, optimizing a fickle infrastructure, and rallying troops around a single vision of building an expansible machine-learning driven product discovery engine. The audience will learn about: -The key technical challenges and outcomes that come with onboarding a solution -The lessons learned of creating and executing operational design -The use of Lucidworks Fusion to plug custom data science models into search and browse applications to understand user intent and deliver personalized experiences

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Knowledge graphs and machine learning are on the rise as enterprises hunt for more effective ways to connect the dots between the data and the business world. With newer technologies, the digital workplace can dramatically improve employee engagement, data-driven decisions, and actions that serve tangible business objectives. In this webinar, you will learn -- Introduction to knowledge graphs and where they fit in the ML landscape -- How breakthroughs in search affect your business -- The key features to consider when choosing a data discovery platform -- Best practices for adopting AI-powered search, with real-world examples

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The document discusses building a business case for enterprise search. It notes that 85% of information is unstructured data locked in various locations and applications. Many knowledge workers spend a significant portion of their day searching across multiple systems for information. The rise of unstructured data and AI capabilities can help organizations unlock value from their information assets. Effective enterprise search powered by AI can provide real-time intelligence, personalized information, and more efficient research to help knowledge workers.

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The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event. The objectives of the Lunch and Learn presentation were to: - Review what KM ‘is’ and ‘isn’t’ - Understand the value of KM and the benefits of engaging - Define and reflect on your “what’s in it for me?” - Share actionable ways you can participate in Knowledge - - Capture & Transfer

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Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless. As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency. We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.

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It's Just Search: Presented by Erik Hatcher, Lucidworks

1. O C T O B E R 1 1 - 1 4 , 2 0 1 6 • B O S T O N , M A

2. It’s Just Search Erik Hatcher Co-founder and Senior Solutions Architect, Lucidworks

3. it’s just search

4. it’s just +search

5. search ?q=

6. search

7. Think inside the box. Inside the search box, that is. The "best"* search results incorporate many more factors than (just) textual matching and relevancy. Search experience owners manage query context rules, signals automatically feed back machine learned factors, users implicit and explicit behaviors ﬁlter and weight future interactions. Synergy emerges with several cooperating (just) searches. This talk will showcase and detail several (just) search examples including rules, typeahead/suggest, signals, and location awareness, bringing them all together into a cohesive search experience. Abstract

8. • Lucene/Solr Committer • Apache Software Foundation Member • Creator of Blacklight • Co-author of “Ant in Action” and “Lucene in Action” • Co-founder and Senior Solutions Architect at Lucidworks About me @erikhatcher

10. anatomy of search results

11. Anatomy of Search Results

12. Anatomy of Search Results Relevancy ranked results

13. Anatomy of Search Results Facets

14. Anatomy of Search Results Highlighting

15. Grouping

16. • relevancy ranked results • faceting • highlighting • grouping (collapsing) • more-like-this • did-you-mean (spellcheck) Search Features

17. typeahead,   autocomplete,   suggest,   instant search

18.

19. spell checking

20.

21. • query a “typed” n-grammed index, and get “typed” results • type examples: brands, categories, specialties, treatments, providers/doctors, products • suggest Things Not Strings • things have attributes: metadata (known) entity detection

22. • /select?q=sea… • q=<what user typed> • Response includes grouped and ranked results, highlighting, and spellcheck suggestions typeahead request

23. signals

24. • clicks and queries • add-to-carts • user history, behavior, and preferences • geo-location, device signals and recommendations

25.

26. signals workﬂow

27. • <collection>/select?q=search • <collection>_signals_aggr/select • ?q=${q} • qf, pf, sort • ==> bq: "id:7^1.0" signals sub-query

28. rules

29. • trigger off query context • query, ﬁlters, date/time, tags • actions - • boost, block, banner, redirect, set parameters,   rewrite query, etc • superset of signals • signals: automated feedback • rules: manually created rules

30.

31.

32. • <collection>/select?q=solr search  [&tags=mobile,production] • <collection>_rules/select • ?q=${q} • &fq=-enabled:false • &fq=…effective_range:$now… • &fq=…tags:($tags)… • process rules returned • manipulate request, append to response rules sub-query

33. geo-lookup

34. • /providers/select?q=jones&zipcode=10301 • /zipcodes/select?q={!term f=zipcode_s v=$zipcode} zipcodes collection zipcodes.csv ZipCode,State,City,County,Latitude,Longitude,AreaCode,TimeZone,DST 85701,AZ,Tucson,Pima,32.216091,-110.97099,520,-7,N 10301,NY,Staten Island,Richmond,40.6226,-74.0992,718,-5,Y 22901,VA,Charlottesville,Albemarle,38.071751,-78.503937,434,-5,Y, fl += dist:geodist() fq += {!geofilt} pt = ${zipcode_doc.latlon_srpt} sfield = locations_rpt d = 10 sort = geodist() asc

35.

36. conclusion

37.

38. •simple things working together •whole is greater than the sum of the parts •feedback loops •emergent behavior Synergy

39.

40. • Presentation materials: • https://github.com/erikhatcher/searchcamp • Search Hub: • http://searchhub.lucidworks.com/ • Fusion (platform used for presentation): • https://lucidworks.com/products/fusion/ See Also @erikhatcher

41.

42. Lucidworks Fusion Is Search-Driven Everything Access data from anywhere to build intelligent, data- driven applications. Data Acquisition Indexing & Streaming Smart Access API Recommendations &  Alerts Analytics & InsightsExtreme Relevancy CUSTOMER SERVICE RESEARCH PORTAL DIGITAL CONTENT CUSTOMER INSIGHTS FRAUD SURVEILLANCE ONLINE  RETAIL

43. • https://commons.wikimedia.org/wiki/File:Ant_bridge.jpg  • http://jillian.rootaction.net/?p=340  • https://commons.wikimedia.org/wiki/ File:Turtles.on.a.stone.in.brazil.jpg image credits

It's Just Search: Presented by Erik Hatcher, Lucidworks

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