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The inbounder London 2. May 2017 Gianluca Fiorelli
The document discusses Google's various products, services, and areas of focus based on the company's patents, research papers, and acquisitions. It notes Google's focus on areas like natural language processing, information retrieval, learning from user interactions, and personalized search. It also lists some of Google's acquisitions and products in areas like video/images, AI/chatbots, VR, and machine learning datasets. The document suggests Google's alphabet includes entities, context, parsing, semantics, and understanding as key areas.
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The inbounder London 2. May 2017 Gianluca Fiorelli
- 2. GIANLUCA FIORELLI THE ALPHABET OF GOOGLEgfiorelli1 #theinbounder
- 3. Everybody wants to bea Jedi gfiorelli1 #theinbounder
- 4. Usually becoming a mere representation of aJedi gfiorelli1 #theinbounder
- 5. The problem is thatwe tend to think tactically gfiorelli1 #theinbounder
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- 7. What does anSEO usually think when asked about Google? gfiorelli1 #theinbounder
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- 11. Inside Search Blog Office Hours Videos Virtual& not Talks Patents/Papers Adquisiciones Rumors Propaganda Fandom New Employees
- 12. APP Indexing Rich Cards Real time Indexing API Webmaster Blog Interstitial AMP Series Reviews inLocal KGraph New AMP Tester More Https PWA Mobile 1st Rich Cards New Mobile Friendly Test API UGC Spam Crawl Budget Google Safe Browsing’s Site Status #Nohacked Similar Item How We Fought Webspam
- 13. APP Indexing Rich Cards Webmaster Blog Interstitial AMP Series New AMP Tester PWA Mobile 1st Rich Cards New Mobile FriendlyTest API May 2016 – January 2017 MOBILE MOBILE MOBILE
- 14. Real time Indexing API Reviews in Local KGraph More Https UGC Spam Crawl Budget GoogleSafe Browsing’s Site Status #Nohacked Similar Item How We Fought Webspam Webmaster Blog
- 15. Research Blog More than 40posts in 5 months. More posts than the Webmaster Blog. And one clear main topic gfiorelli1 #theinbounder
- 16. Patents & Papers SentenceCompression Patent Associating an Entity With a Search Query Methods & Systems For Classifying Data Using a Hierarchical Taxonomy Ranking Events User-Context-Based Search Engine Recommended News On Map With Geo Entities Will Google Start Giving People Social Media Influencer Scores? How Google May Rank Websites Based Upon Their Databases Answering Queries Google’s Related Questions Patent or ‘People Also Ask’ Questions Ranking Local Businesses Based Upon Quality Measures including Travel Time Google May Check to See if People Go to Geographic Locations Google May Recommend Google Introduces a Social Where Next Suggestion Patent Google Search Query Refinements Patent Updated Google and Spoken Queries: Understanding Stressed Pronouns A New Search Results Evaluation Model from Google Answering Featured Snippets Timely, Using Sentence Compression on News Google Patents Context Vectors to Improve Search How Google May Respond to Reverse Engineering of Spam Detection How Google May Map a Query to an Entity for Suggestions gfiorelli1 #theinbounder http://www.seobythesea.com/
- 17. Patents & Papers SentenceCompression Patent Associating an Entity With a Search Query Methods & Systems For Classifying Data Using a Hierarchical Taxonomy Ranking Events User-Context-Based Search Engine Recommended News On Map With Geo Entities Will Google Start Giving People Social Media Influencer Scores? How Google May Rank Websites Based Upon Their Databases Answering Queries Google’s Related Questions Patent or ‘People Also Ask’ Questions Ranking Local Businesses Based Upon Quality Measures including Travel Time Google May Check to See if People Go to Geographic Locations Google May Recommend Google Introduces a Social Where Next Suggestion Patent Google Search Query Refinements Patent Updated Google and Spoken Queries: Understanding Stressed Pronouns A New Search Results Evaluation Model from Google Answering Featured Snippets Timely, Using Sentence Compression on News Google Patents Context Vectors to Improve Search How Google May Respond to Reverse Engineering of Spam Detection How Google May Map a Query to an Entity for Suggestions gfiorelli1 #theinbounder http://www.seobythesea.com/ Entity Search Local Search / Geolocalization Informational Retrieval (old patents updated) Vocal Search Search User Experience
- 18. Patents & Papers InformationRetrieval Learning from User Interactions in Personal Search via Attribute Parameterization Related Event Discovery Situational Context for Ranking in Personal Search Improving topic clustering on search queries with word co-occurrence and bipartite graph co-clustering Incorporating Clicks, Attention and Satisfaction into a Search Engine Result Page Evaluation Model Large-Scale Analysis of Viewing Behavior: Towards Measuring Satisfaction with Mobile Proactive Systems Learning for Efficient Supervised Query Expansion via Two-stage Feature Selection Learning to Rank with Selection Bias in Personal Search M3A: Model, MetaModel, and Anomaly Detection in Web Searches Using Machine Learning to Improve the Email Experience Wide & Deep Learning for Recommender Systems gfiorelli1 #theinbounder
- 19. Learning from UserInteractions in Personal Search via Attribute Parameterization Related Event Discovery Situational Context for Ranking in Personal Search Improving topic clustering on search queries with word co-occurrence and bipartite graph co-clustering Incorporating Clicks, Attention and Satisfaction into a Search Engine Result Page Evaluation Model Large-Scale Analysis of Viewing Behavior: Towards Measuring Satisfaction with Mobile Proactive Systems Learning for Efficient Supervised Query Expansion via Two-stage Feature Selection Learning to Rank with Selection Bias in Personal Search M3A: Model, MetaModel, and Anomaly Detection in Web Searches Using Machine Learning to Improve the Email Experience Wide & Deep Learning for Recommender Systems gfiorelli1 #theinbounder Search User Experience Personalised Search Context Patents & Papers Information Retrieval
- 20. Patents & Papers NaturalLanguage Processing gfiorelli1 #theinbounder About 45 Papers in just 1 year! Generating Long and Diverse Responses with Neural Conversation Models Language Modeling in the Era of Abundant Data Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning A Piggyback System for Joint Entity Mention Detection and Linking in Web Queries Collective Entity Resolution with Multi-Focal Attention Conversational Contextual Cues: The Case of Personalization and History for Response Ranking Exploring the Steps of Verb Phrase Ellipsis
- 21. Patents & Papers NaturalLanguage Processing gfiorelli1 #theinbounder About 45 Papers in just 1 year! Generating Long and Diverse Responses with Neural Conversation Models Language Modeling in the Era of Abundant Data Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning A Piggyback System for Joint Entity Mention Detection and Linking in Web Queries Collective Entity Resolution with Multi-Focal Attention Conversational Contextual Cues: The Case of Personalization and History for Response Ranking Exploring the Steps of Verb Phrase Ellipsis Rhetoric Entity Search Context Personalisation
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- 23. WebPass Moodstock Anvato Kifi Launch Kit Orbitera Apigee Eyefluence Acquisitions & ProductsUrban Engine API.ai Famebit Google Assistant DayDreamVR Google Home Kaggle GBoard Images Video / Video Influencers APP Link Sharing & Recommendations Local / Geolocalization API AI / Chatbots Vocal Search / Natural Language VR Machine Learning / Datasets – Entity Search / Collaborative Coding
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- 32. 1.The average agekids start owning a smartphone is 10.3 years; 2.Children from 5 to 13 years old (and also young people up to 20 years old) tend to me more visual than textual; 3.Their influence on the buying habits of their parents has been known for many years and, in 2012, it was equal to $1.2 trillion USD in spending.
- 35. Similar items: Rich productsfeature on Google Image Search
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- 46. Thinking of localsearch only as MyBusiness optimization may limit the opportunities businesses can have to earn SEO visibility and traffic.
- 47. Checklist: • Identify theEntities related to our niche and how they are connected
- 48. Checklist: • Identify theEntities related to our niche and how they are connected • Match them with our Audience interests
- 49. Checklist: • Identify theEntities related to our niche and how they are connected • Match them with our Audience interests • Content Architecture based on Ontology/Taxonomy based Hubs
- 50. Checklist: • Identify theEntities related to our niche and how they are connected • Match them with our Audience interests • Content Architecture based on Ontology/Taxonomy based Hubs • Do Keywords Research and Mapping with Entities in mind
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- 52. Pizzeria The story The people Theclients The neighbourhood
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- 54. TAG ALL THETHINGS WITH SCHEMA.ORG JSON-LD fired by Tag Manager is better for mobile experience
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- 62. @gfiorelli1 Do not reduce allyour SEO strategy to answering Google Suggests
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- 76. Experiment with GoogleAssistant API https://developers.google.com/action s/
- 79. What about my bills,my sons’ college, my retirement in Spain?
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- 85. Generic but nontrivial knowledge all all marketing disciplines T E C H N I C A L M A R K E T E R S
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- 92. Buyer Persona KW Research Top 10 Ranking Sites *Query Intention Entity Recognition via CNL API Thesaurus Creation
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- 95. Conversions (Direct & Assisted) UserBehaviour SEO Metrics
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