[Show HN: I ranked news websites by speed | Hacker News](https://news.ycombinator.com/item?id=31910622)
[The Speed Report • Legible News](https://legiblenews.com/speed)

[Search engines and SEO spam | Hacker News](https://news.ycombinator.com/item?id=29782186)
[Paul Graham on Twitter: "This may not just be a problem with Google but possibly also the recipe for beating Google. A startup usually has to start with a niche market. Why not try writing a search engine specifically for some category dominated by SEO spam?" / Twitter](https://web.archive.org/web/20220124220557/https://twitter.com/paulg/status/1477760548787920901)

[44 Black Hat SEO Techniques That Will Tank Your Site](https://cognitiveseo.com/blog/12169/44-black-hat-seo-techniques)

[MICES 2022 Mix-camp E-Commerce Search](http://www.mices.co/)
[MIx-Camp E-commerce Search](https://www.youtube.com/channel/UCCxvMykUdtFFc1O_tIr9oxA)

[How to Build a Smart Synonyms Model](https://blog.kensho.com/how-to-build-a-smart-synonyms-model-1d525971a4ee)

[E-Commerce UX Research Articles - Baymard Institute](https://baymard.com/blog)
[9 UX Best Practice Design Patterns for Autocomplete Suggestions (Only 19% Get Everything Right) - Articles - Baymard Institute](https://baymard.com/blog/autocomplete-design)
[Search UX: Autodirect or Guide Users to Matching Category Scopes (46% Get It Wrong) - Articles - Baymard Institute](https://baymard.com/blog/autodirect-searches-matching-category-scopes)
[Product Thumbnails Should Dynamically Update to Match the Variation Searched For (54% Don't) - Articles - Baymard Institute](https://baymard.com/blog/color-and-variation-searches)
[Six 'COVID-19' Related E-Commerce UX Improvements to Make - Articles - Baymard Institute](https://baymard.com/blog/covid-19-ux-improvements)
[Deconstructing E-Commerce Search UX: The 8 Most Common Search Query Types (42% of Sites Have Issues) - Articles - Baymard Institute](https://baymard.com/blog/ecommerce-search-query-types)
[E-Commerce Search Usability: Report & Benchmark - Articles - Baymard Institute](https://baymard.com/blog/ecommerce-search-report-and-benchmark)
[External Article: The Current State of E-Commerce Search - Articles - Baymard Institute](https://baymard.com/blog/external-article-state-of-ecommerce-search)
[Faceted Sorting A New Method for Sorting Search Results - Articles - Baymard Institute](https://baymard.com/blog/faceted-sorting)
[7 Filtering Implementations That Make Macy's Best-in-Class - Articles - Baymard Institute](https://baymard.com/blog/macys-filtering-experience)
[Search UX: 6 Essential Elements for 'No Results' Pages - Articles - Baymard Institute](https://baymard.com/blog/no-results-page)
[E-Commerce Search Field Design and Its Implications - Articles - Baymard Institute](https://baymard.com/blog/search-field-design)
[E-Commerce Sites Need Multiple of These 5 'Search Scope' Features - Articles - Baymard Institute](https://baymard.com/blog/search-scope)
[E-Commerce Sites Should Include Contextual Search Snippets (96% Get it Wrong) - Articles - Baymard Institute](https://baymard.com/blog/search-snippets)
[E-Commerce Search Needs to Support Users' Non-Product Search Queries (15% Don't) - Articles - Baymard Institute](https://baymard.com/blog/support-non-product-search)

[Boosting product discovery with semantic search](https://blog.griddynamics.com/boosting-product-discovery-with-semantic-search)
[Not your father's search engine: a brief history of retail search](https://blog.griddynamics.com/not-your-fathers-search-engine-a-brief-history-of-retail-search)
[Semantic query parsing blueprint](https://blog.griddynamics.com/semantic-query-parsing-blueprint)
[Semantic Vector Search Engine: The New Frontier in Product Discovery](https://blog.griddynamics.com/semantic-vector-search-the-new-frontier-in-product-discovery)
[Smart autocomplete best practices](https://blog.griddynamics.com/smart-autocomplete-best-practices)

[search|hub home](https://www.searchhub.io/)
[How to Achieve Ecommerce Search Relevance](https://blog.searchhub.io/how-to-achieve-ecommerce-search-relevance?cn-reloaded=1&cn-reloaded=1)
[searchhub blog](https://blog.searchhub.io/humans-search-for-things-not-for-strings-2?cn-reloaded=1)
[searchhub blog](https://blog.searchhub.io/the-art-of-abstraction-revisting-webshop-architecture)
[The importance of Synonyms in eCommerce Search](https://blog.searchhub.io/the-importance-of-synonyms-in-ecommerce-search)
[searchhub blog](https://blog.searchhub.io/three-pillars-of-search-quality-in-ecommerce-part-1-findability)
[Part 2: Search Quality for Discovery & Inspiration](https://blog.searchhub.io/three-pillars-of-search-quality-in-ecommerce-part-2-discovery-inspiration)
[A closer look into the spell correction problem - Part 1](https://medium.com/@searchhub.io/a-closer-look-into-the-spell-correction-problem-part-1-a6795bbf7112)
[A closer look into the spell correction problem - Part 2 - introducing preDict](https://medium.com/@searchhub.io/a-closer-look-into-the-spell-correction-problem-part-2-introducing-predict-8993ecab7226)
[A closer look into the spell correction problem - Part 3 - the bells and whistles](https://medium.com/@searchhub.io/a-closer-look-into-the-spell-correction-problem-part-3-the-bells-and-whistles-19697a34011b)
[GitHub searchhub/preDict: Lightning fast spell correction/fuzzy search library based on SymSpell by Commerce-Experts](https://github.com/searchhub/preDict)
[GitHub searchhub/search-collector: A fast and simple JavaScript library specifically targeted at collecting search and search related browser events.](https://github.com/searchhub/search-collector)

[How to Write a Spelling Corrector](http://norvig.com/spell-correct.html)

[Search Optimization 101 How do I know that my search is broken? Supahands](https://blog.supahands.com/2020/07/08/how-do-i-know-that-my-search-is-broken)
[Search Optimization 101 What does it mean if my search is 'broken'? Supahands](https://blog.supahands.com/2020/07/20/search-optimization-101-what-does-it-mean-if-my-search-is-broken)
[Search Optimization 101 How do you fix a broken search? Supahands](https://blog.supahands.com/2020/08/04/search-optimization-101-how-do-you-fix-a-broken-search)
[Search Optimization 101 Reducing business risk by optimizing search Supahands](https://blog.supahands.com/2020/09/02/reducing-business-risks-by-optimizing-search)

[Beginner's Guide to SEO (Search Engine Optimization) - Moz](https://moz.com/beginners-guide-to-seo)

[The Professional's Guide to SEO (Search Engine Optimization) - Moz](https://moz.com/professionals-guide-to-seo)

[SEO Learning Center - Moz](https://moz.com/learn/seo)

[Google Structured Data Intro](https://developers.google.com/search/docs/guides/intro-structured-data)
(mandatory)
[Schema Markup Testing Tool | Google Search Central  |  Google for Developers](https://developers.google.com/search/docs/appearance/structured-data)
[Google Structured Data Examples](https://developers.google.com/search/reference/overview)
(mandatory)

[Google Search Console](https://www.google.com/webmasters/tools/home?hl=en)
Search Console tools and reports help you measure your site's Search traffic and performance, fix issues, and make your site shine in Google Search results.
[Google - Rich Snippet Tester](http://www.google.com/webmasters/tools/richsnippets)
[Google Structured Data Checker](https://www.google.com/webmasters/markup-helper)
This tool will help you add structured-data markup to a sample web page.

[Structured vs Unstructured Data 101: Top Guide | Datamation](https://www.datamation.com/big-data/structured-vs-unstructured-data/)

[A simple spell checker built from word vectors](https://blog.usejournal.com/a-simple-spell-checker-built-from-word-vectors-9f28452b6f26)

[Keyword Extraction using RAKE](https://codelingo.wordpress.com/2017/05/26/keyword-extraction-using-rake)

[Amazon SEO Explained: How to Rank Your Products #1 in 2020](https://crazylister.com/blog/amazon-seo-ultimate-guide)
[Discover How Cassini (The eBay Search Engine) Works and Rank #1](https://crazylister.com/blog/ebay-search-engine-cassini)

[Daniel Tunkelang - Medium](https://medium.com/@dtunkelang)
[A/B Testing for Search is Different](https://medium.com/@dtunkelang/a-b-testing-for-search-is-different-f6b0f6f4d0f5)
[Broad and Ambiguous Search Queries](https://medium.com/@dtunkelang/broad-and-ambiguous-search-queries-1bbbe417dcc)
[Coffee, Coffee, Coffee!](https://medium.com/@dtunkelang/coffee-coffee-coffee-de3121b797d1)
[Evaluating Search: Measure It](https://medium.com/@dtunkelang/evaluating-good-search-part-i-measure-it-5507b2dbf4f6)
[Evaluating Search: Measuring Searcher Behavior](https://medium.com/@dtunkelang/evaluating-search-measuring-searcher-behavior-5f8347619eb0)
[Evaluating Search: Using Human Judgement](https://medium.com/@dtunkelang/evaluating-search-using-human-judgement-fbb2eeba37d9)
[Facets of Faceted Search](https://medium.com/@dtunkelang/facets-of-faceted-search-38c3e1043592)
[Interview Questions for Search Relevance Engineers, Data Scientists, and Product Managers](https://medium.com/@dtunkelang/interview-questions-for-search-relevance-engineers-and-product-managers-7a1b6b8cacea)
[Learning from Friction to Improve the Search Experience](https://medium.com/@dtunkelang/learning-from-friction-to-improve-the-search-experience-8937c71ec97a)
[Query Understanding, Divided into Three Parts](https://medium.com/@dtunkelang/query-understanding-divided-into-three-parts-d9cbc81a5d09)
[Broad and Ambiguous Search Queries](https://dtunkelang.medium.com/broad-and-ambiguous-search-queries-1bbbe417dcc)
[On Search Leadership](https://dtunkelang.medium.com/on-search-leadership-815b36c15df1)
[Searching for Goldilocks](https://dtunkelang.medium.com/searching-for-goldilocks-12cb21c7d036)
[Thoughts on Search Result Diversity](https://dtunkelang.medium.com/thoughts-on-search-result-diversity-1df54cb5bf4a)
[Real Talk About Synonyms and Search](https://medium.com/@dtunkelang/real-talk-about-synonyms-and-search-bb5cf41a8741)
[Search: Intent, Not Inventory](https://medium.com/@dtunkelang/search-intent-not-inventory-289386f28a21)
[Search Queries and Search Intent](https://medium.com/@dtunkelang/search-queries-and-search-intent-1dec79ad155f)
[Shopping is Hard, Let's go Searching!](https://medium.com/@dtunkelang/shopping-is-hard-lets-go-searching-f61f3d5764d3)
[Supporting the Searcher's Journey: When and How](https://medium.com/@dtunkelang/supporting-the-searchers-journey-when-and-how-568e9b68fe02)
[Thoughts about Managing Search Teams](https://medium.com/@dtunkelang/thoughts-about-managing-search-teams-f8d2f54fbed7)
[When There's No Conversion Rate](https://medium.com/@dtunkelang/when-theres-no-conversion-rate-67a372666fed)
[Why is it so hard to sort by price?](https://medium.com/@dtunkelang/why-is-it-so-hard-to-sort-by-price-2a5e63899233)

[Food Discovery with Uber Eats: Building a Query Understanding Engine | Uber Blog](https://eng.uber.com/uber-eats-query-understanding)

[Search Relevance Solr,Elasticsearch,OpenSearch Training & Consulting](https://www.opensourceconnections.com/)
[How to Implement a Normalized Discounted Cumulative Gain (NDCG) Ranking Quality Scorer in Quepid OpenSource Connections](https://opensourceconnections.com/blog/2018/02/26/ndcg-scorer-in-quepid)
[BM25 The Next Generation of Lucene Relevance OpenSource Connections](https://opensourceconnections.com/blog/2015/10/16/bm25-the-next-generation-of-lucene-relevation)
[What is Learning To Rank? OpenSource Connections](https://opensourceconnections.com/blog/2017/02/24/what-is-learning-to-rank)
[How is search different than other machine learning problems? OpenSource Connections](https://opensourceconnections.com/blog/2017/08/03/search-as-machine-learning-prob)
[An Introduction to Search Quality OpenSource Connections](https://opensourceconnections.com/blog/2018/11/19/an-introduction-to-search-quality)
[The Unreasonable Effectiveness of Collocations OpenSource Connections](https://opensourceconnections.com/blog/2019/05/16/unreasonable-effectiveness-of-collocations)
[Falsehoods Programmers Believe About Search OpenSource Connections](https://opensourceconnections.com/blog/2019/05/29/falsehoods-programmers-believe-about-search)
[Understanding BERT and Search Relevance OpenSource Connections](https://opensourceconnections.com/blog/2019/11/05/understanding-bert-and-search-relevance)
[Demystifying nDCG and ERR OpenSource Connections](https://opensourceconnections.com/blog/2019/12/09/demystifying-ndcg-and-err)
[What is a 'Relevant' Search Result? OpenSource Connections](https://opensourceconnections.com/blog/2019/12/11/what-is-a-relevant-search-result)
[Choosing your search relevance evaluation metric OpenSource Connections](https://opensourceconnections.com/blog/2020/02/28/choosing-your-search-relevance-metric)
[Feedback debt: what the Segway teaches search teams OpenSource Connections](https://opensourceconnections.com/blog/2020/03/19/feedback-debt)
[5 Right Ways to Measure How Search Is Performing OpenSource Connections](https://opensourceconnections.com/blog/2020/05/11/5-right-ways-to-measure-search)
[Building an Effective Search Team: the key to great search & relevancy OpenSource Connections](https://opensourceconnections.com/blog/2020/05/14/building-an-effective-search-team-the-key-to-great-search-relevancy)
[E-commerce Site-Search KPIs Part 1 Customers OpenSource Connections](https://opensourceconnections.com/blog/2020/08/28/e-commerce-site-search-kpis)
[E-commerce Site-Search KPIs Part 2 Products OpenSource Connections](https://opensourceconnections.com/blog/2020/09/10/e-commerce-site-search-kpis-part-2)
[E-Commerce Site-Search KPIs Part 3 Queries OpenSource Connections](https://opensourceconnections.com/blog/2020/09/24/e-commerce-site-search-kpis-part-3-queries)
[Fundamentals of query rewriting (part 1): introduction to query expansion OpenSource Connections](https://opensourceconnections.com/blog/2021/10/19/fundamentals-of-query-rewriting-part-1-introduction-to-query-expansion)
[OpenSource Connections](https://www.youtube.com/channel/UCiuXt-f2Faan4Es37nADUdQ)

[Discounted cumulative gain Wikipedia](https://en.wikipedia.org/wiki/Discounted_cumulative_gain)

[Evaluation measures (information retrieval) Wikipedia](https://en.wikipedia.org/wiki/Evaluation_measures_(information_retrieval)#Precision_at_K)

[F-score Wikipedia](https://en.wikipedia.org/wiki/F1_score)

[Mean reciprocal rank Wikipedia](https://en.wikipedia.org/wiki/Mean_reciprocal_rank)

[Doug Turnbull (@softwaredoug)/Twitter](https://twitter.com/softwaredoug)
[What is Presentation Bias in search?](https://softwaredoug.com/blog/2022/07/16/what-is-presentation-bias-in-search.html)
[Compute Mean Reciprocal Rank (MRR) using Pandas](https://softwaredoug.com/blog/2021/04/21/compute-mrr-using-pandas.html)

[Personal data Wikipedia](https://en.wikipedia.org/wiki/Personal_data)

[Precision and recall Wikipedia](https://en.wikipedia.org/wiki/Precision_and_recall)

[If I Only Had an (Enterprise Search) Brain: Behind the Wizardry of a Seamless Search Experience Enterprise Knowledge](https://enterprise-knowledge.com/if-i-only-had-an-enterprise-search-brain-behind-the-wizardry-of-a-seamless-search-experience)
[Optimizing Your Search Experience: A Human-Centered Approach to Search Design Enterprise Knowledge](https://enterprise-knowledge.com/optimizing-your-search-experience-a-human-centered-approach-to-search-design)
[The Role of Search Product Owners Enterprise Knowledge](https://enterprise-knowledge.com/the-role-of-search-product-owners)
[Integrating Search and Knowledge Graphs Series Part 1: Displaying Relationships Enterprise Knowledge](https://enterprise-knowledge.com/integrating-search-and-knowledge-graphs-series-part-1-displaying-relationships)

[Patterns for Personalization in Recommendations and Search](https://eugeneyan.com/writing/patterns-for-personalization)

[data-science-interviews/theory.md at master · alexeygrigorev/data-science-interviews](https://github.com/alexeygrigorev/data-science-interviews/blob/master/theory.md#ranking-andsearch)

[GitHub frutik/awesome-e-commerce](https://github.com/frutik/awesome-e-commerce)
[sandbox Jan 2020 · Issue #1 · frutik/awesome-search](https://github.com/frutik/awesome-search/issues/1)
[sandbox Dec 2020 · Issue #10 · frutik/awesome-search](https://github.com/frutik/awesome-search/issues/10)
[sandbox April 2021 · Issue #17 · frutik/awesome-search](https://github.com/frutik/awesome-search/issues/17)
[sandbox May 2021 · Issue #18 · frutik/awesome-search](https://github.com/frutik/awesome-search/issues/18)
[sandbox Jun 2021 · Issue #19 · frutik/awesome-search](https://github.com/frutik/awesome-search/issues/19)

[SymSpell vs. BK-tree: 100x faster fuzzy string search & spell checking](https://towardsdatascience.com/symspell-vs-bk-tree-100x-faster-fuzzy-string-search-spell-checking-c4f10d80a078)

[Contextual Query Understanding: An Overview](https://queryunderstanding.com/contextual-query-understanding-65c78d792dd8)
[Query Understanding and Chatbots](https://queryunderstanding.com/query-understanding-and-chatbots-5fa0c154f)
[Query Understanding and Voice Interfaces](https://queryunderstanding.com/query-understanding-and-voice-interfaces-6cd60d063fca)
[Autocomplete](https://queryunderstanding.com/autocomplete-69ed81bba245)
[Autocomplete and User Experience](https://queryunderstanding.com/autocomplete-and-user-experience-421df6ab3000)
[Character Filtering](https://queryunderstanding.com/character-filtering-76ede1cf1a97)
[Clarification Dialogues](https://queryunderstanding.com/clarification-dialogues-69420432f451)
[Entity Recognition](https://queryunderstanding.com/entity-recognition-763cae840a20)
[Faceted Search](https://queryunderstanding.com/faceted-search-7d053cc4fada)
[Location as Context](https://queryunderstanding.com/geographical-context-77ce4c773dc7)
[Query Understanding: An Introduction](https://queryunderstanding.com/introduction-c98740502103)
[Language Identification](https://queryunderstanding.com/language-identification-c1d2a072eda)
[Personalization](https://queryunderstanding.com/personalization-3ed715e05ef)
[Query Expansion](https://queryunderstanding.com/query-expansion-2d68d47cf9c8)
[Query Relaxation](https://queryunderstanding.com/query-relaxation-342bc37ad425)
[Query Rewriting: An Overview](https://queryunderstanding.com/query-rewriting-an-overview-d7916eb94b83)
[Query Scoping](https://queryunderstanding.com/query-scoping-ed61b5ec8753)
[Query Segmentation](https://queryunderstanding.com/query-segmentation-2cf860ade503)
[Question Answering](https://queryunderstanding.com/question-answering-94984185c203)
[Relevance Feedback](https://queryunderstanding.com/relevance-feedback-c6999529b92c)
[Search as a Conversation](https://queryunderstanding.com/search-as-a-conversation-bafa7cd0c9a5)
[Search Result Snippets](https://queryunderstanding.com/search-result-snippets-e8c447950219)
[Search Results Clustering](https://queryunderstanding.com/search-results-clustering-b2fa64c6c809)
[Search Results Presentation](https://queryunderstanding.com/search-results-presentation-7d6c6c384ec1)
[Seasonality](https://queryunderstanding.com/seasonality-5eef79d8bf1c)
[Session Context](https://queryunderstanding.com/session-context-4af0a355c94a)
[Spelling Correction](https://queryunderstanding.com/spelling-correction-471f71b19880)
[Stemming and Lemmatization](https://queryunderstanding.com/stemming-and-lemmatization-6c086742fe45)
[Taxonomies and Ontologies](https://queryunderstanding.com/taxonomies-and-ontologies-8e4812a79cb2)
[Tokenization](https://queryunderstanding.com/tokenization-c8cdd6aef7ff)

[AI for Query Understanding](https://www.linkedin.com/pulse/ai-query-understanding-daniel-tunkelang)
[Balance Your Search Budget!](https://www.linkedin.com/pulse/balance-your-search-budget-daniel-tunkelang)
[Opportunity Analysis for Search](https://www.linkedin.com/pulse/opportunity-analysis-search-daniel-tunkelang)
[In Search of Recall](https://www.linkedin.com/pulse/search-recall-daniel-tunkelang)

[Sease Information Retrieval Applied [Consulting, Trainings and Guides]](https://sease.io/)
[Train and Test Sets Split for Evaluating Learning To Rank Models](https://sease.io/2022/07/how-to-split-your-dataset-into-train-and-test-sets-for-evaluating-learning-to-rank-models.html)

[Learning to Rank for Flight Itinerary Search | HackerNoon](https://hackernoon.com/learning-to-rank-for-flight-itinerary-search-8594761eb867)

[Autocomplete, Live Search Suggestions, and Autocorrection: Best Practice Design Patterns](https://hybrismart.com/2019/01/08/autocomplete-live-search-suggestions-autocorrection-best-practice-design-patterns)
[Facet Search: The Most Comprehensive Guide. Best Practices, Design Patterns, Hidden Caveats, And Workarounds.](https://hybrismart.com/2019/02/13/facet-search-the-most-comprehensible-guide-best-practices-design-patterns#d5)

[https://machinelearnings.co/deep-spelling-9ffef96a24f6](https://machinelearnings.co/deep-spelling-9ffef96a24f6)

[A/B Testing Search: thinking like a scientist](https://medium.com/@jamesrubinstein/a-b-testing-search-thinking-like-a-scientist-1cc34b88392e)
[Measuring Search, A Human Approach](https://medium.com/@jamesrubinstein/measuring-search-a-human-approach-acf54e2cf33d)
[Measuring Search: Metrics Matter](https://medium.com/@jamesrubinstein/measuring-search-metrics-matter-de124c2f6f8c)
[Query Triage: The Secret Weapon for Search Relevance](https://medium.com/@jamesrubinstein/query-triage-the-secret-weapon-for-search-relevance-1a02cdd297ed)
[Setting up a relevance evaluation program](https://medium.com/@jamesrubinstein/setting-up-a-relevance-evaluation-program-c955d32fba0e)
[Statistical and human-centered approaches to search engine improvement](https://medium.com/@jamesrubinstein/statistical-and-human-centered-approaches-to-search-engine-improvement-52af0e98f38f)
[The Launch Review: bringing it all together …](https://medium.com/@jamesrubinstein/the-launch-review-bringing-it-all-together-2f7e4cfbf86e)
[Search Product Management: The Most Misunderstood Role in Search?](https://jamesrubinstein.medium.com/search-product-management-the-most-misunderstood-role-in-search-2b7569058638)

[Understanding the Search Query - Part II](https://medium.com/analytics-vidhya/understanding-the-search-query-part-ii-44d18892283f)

[Understanding the Search Query - Part III](https://medium.com/@sonusharma.mnnit/understanding-the-search-query-part-iii-a0c5637a639)

[Synonyms and Antonyms from WordNet](https://medium.com/@tameremil/synonyms-and-antonyms-from-wordnet-778f6274fb09)

[Evaluating & Addressing Position Bias in Adobe Stock Search](https://medium.com/adobetech/evaluating-addressing-position-bias-in-adobe-stock-search-9807b11ee268)

[Building a Better Search Engine for Semantic Scholar](https://medium.com/ai2-blog/building-a-better-search-engine-for-semantic-scholar-ea23a0b661e7)

[Listing Embeddings in Search Ranking](https://medium.com/airbnb-engineering/listing-embeddings-for-similar-listing-recommendations-and-real-time-personalization-in-search-601172f7603e)
[Machine Learning-Powered Search Ranking of Airbnb Experiences](https://medium.com/airbnb-engineering/machine-learning-powered-search-ranking-of-airbnb-experiences-110b4b1a0789)

[FoodDiscovery#2: Ethical Search: Designing an irresistible journey with a positive impact](https://medium.com/empathyco/fooddiscovery-2-ethical-search-designing-an-irresistible-journey-with-a-positive-impact-cc921c07a5a8)
[How to implement faceted search the right way](https://medium.com/empathyco/how-to-implement-faceted-search-the-right-way-4bfba2bd2adc)
[Improving Search Suggestions for eCommerce](https://medium.com/empathyco/improving-search-suggestions-for-ecommerce-cb1bc2946021)
[Synonyms in Solr I - The good, the bad and the ugly](https://medium.com/empathyco/synonyms-in-solr-i-the-good-the-bad-and-the-ugly-efe8e437a940)
[The influence of TF-IDF algorithms in eCommerce search](https://medium.com/empathyco/the-influence-of-tf-idf-algorithms-in-ecommerce-search-e7cb9ab8e662)

[NLP: Text Data To Numbers](https://medium.com/fintechexplained/nlp-text-data-to-numbers-d28d32294d2e)

[On Semantic Search](https://medium.com/modern-nlp/semantic-search-fuck-yeah-e371c0f639d)

[Dive into WordNet with NLTK](https://medium.com/parrot-prediction/dive-into-wordnet-with-nltk-b313c480e788)

[Autosuggest Ranking](https://medium.com/related-works-inc/autosuggest-ranking-d8a3242c2837)
[Autosuggest Retrieval Data Structures & Algorithms](https://medium.com/related-works-inc/autosuggest-retrieval-data-structures-algorithms-3a902c74ffc8)
[Bootstrapping Autosuggest](https://medium.com/related-works-inc/bootstrapping-autosuggest-c1ca3edaf1eb)
[Building an Autosuggest Corpus, Part 2](https://medium.com/related-works-inc/building-an-autosuggest-corpus-nlp-d21b0f25c31b)
[Building an Autosuggest Corpus, Part 1](https://medium.com/related-works-inc/building-an-autosuggest-corpus-part-1-3acd26056708)

[Reinforcement learning assisted search ranking](https://medium.com/sajari/reinforcement-learning-assisted-search-ranking-a594cdc36c29)

[Search is a Team Sport](https://medium.com/search-in-21st-century/search-is-a-team-sport-400eecdfe736)

[Metadata and Faceted Search](https://medium.com/searchblox/metadata-and-faceted-search-62ec6e4de353)
[Autosuggest for Search : Query-based vs. Content-based](https://web.archive.org/web/20181207194952/https://www.searchblox.com/autosuggest-search-query-based-vs-content-based)
[How to Gain Insight From Search Analytics | SearchBlox](https://www.searchblox.com/how-to-gain-insight-from-search-analytics)

[Applying Context Aware Spell Checking in Spark NLP](https://medium.com/spark-nlp/applying-context-aware-spell-checking-in-spark-nlp-3c29c46963bc)

[Visualizing search metrics](https://nathanday.shinyapps.io/rank-algo-app)

[Do all-stopword queries matter?](https://observer.wunderwood.org/2007/05/31/do-all-stopword-queries-matter)

[Metacrap](https://people.well.com/user/doctorow/metacrap.htm)

[Hybrid search > sum of its parts? Berlin Buzzwords 2022](https://pretalx.com/bbuzz22/talk/YEHRTE)

[On-site search design patterns for e-commerce: schema structure, data driven ranking & more](https://project-a.github.io/on-site-search-design-patterns-for-e-commerce)

[5 Searchandising Hacks to Increase Ecommerce Sales](https://searchanise.io/blog/searchandising)

[Search at Slack Slack Engineering](https://slack.engineering/search-at-slack-431f8c80619e)

[Click Modeling for eCommerce](https://tech.ebayinc.com/engineering/click-modeling-for-ecommerce)
[Using Behavioral Data to Improve Search](https://tech.ebayinc.com/engineering/using-behavioral-data-to-improve-search)

[OLX](http://www.olx.com/)
[AutoSuggest Retrieval & Ranking (Part 2)](https://tech.olx.com/autosuggest-retrieval-ranking-part-2-14a8f50fef34)
[Building Corpus for AutoSuggest (Part 1)](https://tech.olx.com/building-corpus-for-autosuggest-part-1-4f63512b1ea1)

[Autocorrect in Google, Amazon and Pinterest and how to write your own one](https://towardsdatascience.com/autocorrect-in-google-amazon-and-pinterest-and-how-to-write-your-own-one-6d23bc927c81)

[E-commerce Search Re-Ranking as a Reinforcement Learning Problem](https://towardsdatascience.com/e-commerce-search-re-ranking-as-a-reinforcement-learning-problem-a9d1561edbd0)
[Embedding for spelling correction](https://towardsdatascience.com/embedding-for-spelling-correction-92c93f835d79)
[Fast Word Segmentation of Noisy Text](https://towardsdatascience.com/fast-word-segmentation-for-noisy-text-2c2c41f9e8da)
[Query Segmentation and Spelling Correction](https://towardsdatascience.com/query-segmentation-and-spelling-correction-483173008981)
[Synonyms and Antonyms in Python](https://towardsdatascience.com/synonyms-and-antonyms-in-python-a865a5e14ce8)
[Locality Sensitive Hashing](https://towardsdatascience.com/understanding-locality-sensitive-hashing-49f6d1f6134)
[Understanding the Search Query - Part I](https://towardsdatascience.com/understanding-the-search-query-part-i-632d1b323b50)
[When to use a machine learned vs. score-based search ranker](https://towardsdatascience.com/when-to-use-a-machine-learned-vs-score-based-search-ranker-aa8762cd9aa9)

[Search Patterns: Design for Discovery](https://searchpatterns.org/)

[Max Irwin (@binarymax) / X](https://x.com/binarymax)

[A.I. for Search | E-commerce Search by 904Labs](https://www.904labs.com/en/blog-google-kills-instant-search.html)

[Interactions with Search Systems](https://www.cambridge.org/core/books/interactions-with-search-systems/5B3CF5920355A8B09088F2C409FFABDC)

[Practical BM25 Part 2: The BM25 Algorithm and its Variables](https://www.elastic.co/blog/practical-bm25-part-2-the-bm25-algorithm-and-its-variables)

[How not to sort by average rating (2009) | Hacker News](https://news.ycombinator.com/item?id=29200103)
[How Not To Sort By Average Rating - Evan Miller](https://www.evanmiller.org/how-not-to-sort-by-average-rating.html)

[Google is improving web search with BERT - can we use it for enterprise search too?](https://www.linkedin.com/pulse/google-improving-web-search-bert-can-we-use-too-mickel-gr%C3%B6nroos)
[Humans - Search for Things not for Strings](https://www.linkedin.com/pulse/humans-search-things-strings-andreas-wagner)

[why we've developed the searchhub smartSuggest module and why it might matter to you](https://www.linkedin.com/pulse/why-weve-developed-searchhub-smartsuggest-module-might-andreas-wagner)

[Relevant Search](https://www.manning.com/books/relevant-search)

[Good Abandonment on Search Results Pages](https://www.nngroup.com/articles/good-abandonment)
[The Love-at-First-Sight Gaze Pattern on Search-Results Pages](https://www.nngroup.com/articles/love-at-first-sight-pattern)
[Complex Search-Results Pages Change Search Behavior: The Pinball Pattern](https://www.nngroup.com/articles/pinball-pattern-search-behavior)
[Scoped Search: Dangerous, but Sometimes Useful](https://www.nngroup.com/articles/scoped-search)
[Search-Log Analysis: The Most Overlooked Opportunity in Web UX Research](https://www.nngroup.com/articles/search-log-analysis)
[3 Guidelines for Search Engine "No Results" Pages](https://www.nngroup.com/articles/search-no-results-serp)
[Site Search Suggestions](https://www.nngroup.com/articles/site-search-suggestions)

[A Face Is Exposed for AOL Searcher No. 4417749 (Published 2006)](https://www.nytimes.com/2006/08/09/technology/09aol.html)

[Types of Information Collections - philosophe.*](https://www.philosophe.com/archived_content/search_topics/collections.html)
[Assumptions About Search - philosophe.*](https://www.philosophe.com/archived_content/search_topics/search_assumptions.html)
[Useful Search Links and References - philosophe.*](https://www.philosophe.com/archived_content/search_topics/search_links.html)
[Users and the Task of Information Retrieval - philosophe.*](https://www.philosophe.com/archived_content/search_topics/search_tasks.html)
[Testing Search - philosophe.*](https://www.philosophe.com/archived_content/search_topics/search_tests.html)
[Considering Search: Search Topics - philosophe.*](https://www.philosophe.com/archived_content/search_topics/search_topics.html)
[A Structural Look at Search - philosophe.*](https://www.philosophe.com/archived_content/search_topics/structure.html)
[Assumptions About User Search Behavior - philosophe.*](https://www.philosophe.com/archived_content/search_topics/user_behavior.html)

[What are some algorithms of spelling correction that are used by search engines? For example, when I used Google to search "Google imeges...](https://www.quora.com/String-Searching-Algorithms/What-are-some-algorithms-of-spelling-correction-that-are-used-by-search-engines-For-example-when-I-used-Google-to-search-Google-imeges-it-prompted-me-Did-you-mean-Google-images/answer/Wolf-Garbe)

[Writing a full-text search engine using Bloom filters Stavros' Stuff](https://www.stavros.io/posts/bloom-filter-search-engine)

[The Age of PageRank Is Over | Hacker News](https://news.ycombinator.com/item?id=33537513)
[The Age of PageRank is Over [manifesto] | Kagi Blog](https://blog.kagi.com/age-pagerank-over)

## search engines list
Google
Bing
Yahoo! Search
AltaVista
Cuil
Excite
Go.com
HotBot
AllTheWeb
GalaxyUniversity of Texas, Austin
AOL Search
Live Search
Lycos
Gigablast
Alexa

## winning at YouTube


I spent basically 5 years of my life locked in a room studying virality on Youtube. Some days me and some other nerds would spend 20 hours straight studying the most minor thing: like is there a correlation between better lighting at the start of the video and less viewer drop off (there is, have good lighting at the start of the video haha) or other tiny things like that. And the result of those probably 20,000 to 30,000 hours of studying is I’d say I have a good grasp on what makes Youtube videos do well. The three metrics you guys need to care about is Click Thru Rate (CTR), Average View Duration (AVD), and Average View Percentage (AVP).

## video marketing

[DIY Sourcing like those Cheesy Make your own Slime Videos but way Nerdier Greg Hawkes](https://www.sourcecon.com/diy-sourcing-like-those-cheesy-make-your-own-slime-videos-but-way-nerdier)

[Evolve of Die Arron Daniels](https://www.sourcecon.com/evolve-or-die)

[I finally created my own video messaging for sourcing Erin Mathew](https://www.sourcecon.com/i-finally-created-my-own-video-messaging-for-sourcing-heres-what-happened)

[Integrating Video into Outreach  Greg Hawkes](https://www.sourcecon.com/integrating-video-into-outreach)

[Using Videos to Source  Josef Kadlec](https://www.sourcecon.com/video-sourcing)

## clickbait and spam

[Google is declaring war on clickbait — but who’s winning? @ AskWoody](https://www.askwoody.com/2024/google-is-declaring-war-on-clickbait-but-whos-winning/)