This document provides an overview of Google BERT and what it means for SEOs and marketers. Some key points:
- BERT uses bidirectional transformers to better understand the context of words in search queries and content. It helps Google resolve ambiguity and understand nuanced language.
- BERT was first introduced as an academic research paper in 2018 and was quickly adopted by Google and other major tech companies to improve natural language understanding.
- While BERT only impacts around 10% of queries, it represents a major improvement in Google's ability to understand user intent and has important implications for SEO, international search, and conversational search.
What is BERT? It is Google's neural network-based technique for natural language processing (NLP) pre-training. BERT stands for Bidirectional Encoder Representations from Transformers. It was opened-sourced last year and written about in more detail on the Google AI blog. In this presentation we look at what Google BERT means for SEOs and marketers and how Google BERT is and will continue to impact the search landscape. We also look at the back story to Google BERT, including transformers and natural language understanding and computational linguistics.
Google BERT and Family and the Natural Language Understanding Leaderboard RaceDawn Anderson MSc DigM
Natural Language Understanding and Word Sense Disambiguation remains one of the prevailing challenges for both conversational and written word. Natural language understanding attempts to untangle the 'hot mess' of words between more structured data in content, but the challenge is not trivial, since there is so much polysemy in language. Some recent developments in machine learning have seen significant leaps forward in understanding more clearly the context (and therefore user intent and informational need at time of query). Here we will explore these developments, and some of their implementations and seek to understand what this means for search strategists and the brands they support both now and into the future.
Natural Language Processing and Search Intent Understanding C3 Conductor 2019...Dawn Anderson MSc DigM
This talk looks at the ways in which search engines are evolving to understand further the nuance of linguistics in natural language processing and in understanding searcher intent.
As the volume of content continues to grow exponentially helping search engines to understand context and the topical themes within your site is increasingly important. Understanding some of the concepts are covered and also ways to utilise these in your marketing strategy.
Talk from Tech SEO Boost 2019 by Dawn Anderson on the move to the just in time predictive personalised search experience for search engines and users. Exploring recommender systems, collaborative filtering, temporal and location based queries and the rise of predictive, personal dynamic search. Exploring the work of information retrieval researchers and Google Discover.
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Tra...Edureka!
** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course **
This Edureka PPT will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics.
The following topics covered in this PPT:
1. The Evolution of Human Language
2. What is Text Mining?
3. What is Natural Language Processing?
4. Applications of NLP
5. NLP Components and Demo
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What is BERT? It is Google's neural network-based technique for natural language processing (NLP) pre-training. BERT stands for Bidirectional Encoder Representations from Transformers. It was opened-sourced last year and written about in more detail on the Google AI blog. In this presentation we look at what Google BERT means for SEOs and marketers and how Google BERT is and will continue to impact the search landscape. We also look at the back story to Google BERT, including transformers and natural language understanding and computational linguistics.
Google BERT and Family and the Natural Language Understanding Leaderboard RaceDawn Anderson MSc DigM
Natural Language Understanding and Word Sense Disambiguation remains one of the prevailing challenges for both conversational and written word. Natural language understanding attempts to untangle the 'hot mess' of words between more structured data in content, but the challenge is not trivial, since there is so much polysemy in language. Some recent developments in machine learning have seen significant leaps forward in understanding more clearly the context (and therefore user intent and informational need at time of query). Here we will explore these developments, and some of their implementations and seek to understand what this means for search strategists and the brands they support both now and into the future.
Natural Language Processing and Search Intent Understanding C3 Conductor 2019...Dawn Anderson MSc DigM
This talk looks at the ways in which search engines are evolving to understand further the nuance of linguistics in natural language processing and in understanding searcher intent.
As the volume of content continues to grow exponentially helping search engines to understand context and the topical themes within your site is increasingly important. Understanding some of the concepts are covered and also ways to utilise these in your marketing strategy.
Talk from Tech SEO Boost 2019 by Dawn Anderson on the move to the just in time predictive personalised search experience for search engines and users. Exploring recommender systems, collaborative filtering, temporal and location based queries and the rise of predictive, personal dynamic search. Exploring the work of information retrieval researchers and Google Discover.
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Tra...Edureka!
** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course **
This Edureka PPT will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics.
The following topics covered in this PPT:
1. The Evolution of Human Language
2. What is Text Mining?
3. What is Natural Language Processing?
4. Applications of NLP
5. NLP Components and Demo
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
How is mobile technology and search engine tuning evolving to meet the needs of users? Here we look at recent developments in research, implementations by search engines, and how to look at reach users can adapt their strategies to take into account these next-level changes.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Adam Bittlingmayer is a technical co-founder at Signal N (http://signaln.com), where he works on sentence-level quality estimation of machine translation.
More about our meetup:
http://www.meetup.com/de-DE/Berlin-Language-Technology/events/228344365/
Introduction to Natural Language ProcessingPranav Gupta
the presentation gives a gist about the major tasks and challenges involved in natural language processing. In the second part, it talks about one technique each for Part Of Speech Tagging and Automatic Text Summarization
SearchLove London 2019 - Rory Truesdale - Using the SERPs to Know Your AudienceDistilled
It’s easy to get swept away by monthly search volume and to forget that behind every search there is a person with a specific motivation and set of needs to fulfil. This talk will look at how you can use Google’s algorithmic rewriting of the SERPs to help you identify those motivations so you can effectively optimise for intent and query context to improve the ranking performance of your landing pages. This talk will also help you understand how you can use this information to create more tailored online experiences for your prospective customers and how the same workflows can be applied for more general business intelligence insights.
Datascope: Designing your Data Viz - The (Iterative) ProcessMollie Pettit
This talk was given to a Data Visualization course, which is part of the Masters of Science in Analytics program at the Northwestern School of Engineering.
It walks through:
- Why to visualize data
- A common (linear) approach to data problems
- A look at a problem in an ambiguos world, and why the linear approach does not always get one to their ideal end point
- A better (iterative) approach
- how to get started on a project through the important practice of brainstorming
-An informal project example. In this example, an iterative approach to the visualization helped the creator to gain new insights which changed her story's focus all-together.
-A case study of a project done for Procter & Gamble. In this example, an iterative approach redirected us from a more complicated network graph of the company (which we initially assumed would be an end-result) to displaying data in a simpler way (e.g. bar charts), which was more ideal for the client.
-Another case study. In this example, an iterative approach led us to create a less obvious / more creative visualization that stressed the things that were most important to the client. Nearly every single iteration step (all of which were shown to the client) are shown in the slides.
It ends with a reminder that doing is better than planning. You really can't learn what your ideal end-product will be until you get started; while working, one must constantly ask questions and gain feedback, and refine the approach accordingly.
One of the biggest challenges in the data age is overcoming the problematic belief that data has all the answers. The truth is – data is a resource, not a solution. In order to extract valuable and actionable insights, it is necessary to ask and re-ask certain questions. This talk is about figuring out what these questions are and exposes some of the limitations of common, and seemingly intuitive, approaches to data problems. As an alternative, I introduce the concept of using human-centered design principles and an iterative process to approach what you do with Big (and small) Data. As exemplars, I will walk-through a quick informal example and a real Datascope client project to highlight the flexibility and speed of these techniques.
Natural Language Processing: L01 introductionananth
This presentation introduces the course Natural Language Processing (NLP) by enumerating a number of applications, course positioning, challenges presented by Natural Language text and emerging approaches to topics like word representation.
Metaphic or the art of looking another way.Suresh Manian
For all intents and purposes, we are our words. And verbs and adjectives capture actions and sentiments better than any other tool. Metaphic is premised on the belief that a grammar book and a calculator are all you really need to make sense of web search and social media chatter, apart from all text, in general.
Mria Pia tackled the terminology trends and shared some interesting examples from her professional experience as a blogger:
1. Communicating about terminology by using social networks.
2. Social networks as available data for carrying out terminology research, in particular for monitoring language changes such as neologisms. More and more researchers are beginning to work on projects consisting in analyzing tweets to catch the next most popular word.
3. Websites are made of content and terminology is the critical part of the user experience.
4. Managing and sharing terminological data: cloud based, collaborative and social platforms.
5. The subject field of terminology is overwhelming, so some websites provide terminological resources in few clicks.
How is mobile technology and search engine tuning evolving to meet the needs of users? Here we look at recent developments in research, implementations by search engines, and how to look at reach users can adapt their strategies to take into account these next-level changes.
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With ...Edureka!
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural... ** )
This PPT will provide you with detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this PPT:
Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Adam Bittlingmayer is a technical co-founder at Signal N (http://signaln.com), where he works on sentence-level quality estimation of machine translation.
More about our meetup:
http://www.meetup.com/de-DE/Berlin-Language-Technology/events/228344365/
Introduction to Natural Language ProcessingPranav Gupta
the presentation gives a gist about the major tasks and challenges involved in natural language processing. In the second part, it talks about one technique each for Part Of Speech Tagging and Automatic Text Summarization
SearchLove London 2019 - Rory Truesdale - Using the SERPs to Know Your AudienceDistilled
It’s easy to get swept away by monthly search volume and to forget that behind every search there is a person with a specific motivation and set of needs to fulfil. This talk will look at how you can use Google’s algorithmic rewriting of the SERPs to help you identify those motivations so you can effectively optimise for intent and query context to improve the ranking performance of your landing pages. This talk will also help you understand how you can use this information to create more tailored online experiences for your prospective customers and how the same workflows can be applied for more general business intelligence insights.
Datascope: Designing your Data Viz - The (Iterative) ProcessMollie Pettit
This talk was given to a Data Visualization course, which is part of the Masters of Science in Analytics program at the Northwestern School of Engineering.
It walks through:
- Why to visualize data
- A common (linear) approach to data problems
- A look at a problem in an ambiguos world, and why the linear approach does not always get one to their ideal end point
- A better (iterative) approach
- how to get started on a project through the important practice of brainstorming
-An informal project example. In this example, an iterative approach to the visualization helped the creator to gain new insights which changed her story's focus all-together.
-A case study of a project done for Procter & Gamble. In this example, an iterative approach redirected us from a more complicated network graph of the company (which we initially assumed would be an end-result) to displaying data in a simpler way (e.g. bar charts), which was more ideal for the client.
-Another case study. In this example, an iterative approach led us to create a less obvious / more creative visualization that stressed the things that were most important to the client. Nearly every single iteration step (all of which were shown to the client) are shown in the slides.
It ends with a reminder that doing is better than planning. You really can't learn what your ideal end-product will be until you get started; while working, one must constantly ask questions and gain feedback, and refine the approach accordingly.
One of the biggest challenges in the data age is overcoming the problematic belief that data has all the answers. The truth is – data is a resource, not a solution. In order to extract valuable and actionable insights, it is necessary to ask and re-ask certain questions. This talk is about figuring out what these questions are and exposes some of the limitations of common, and seemingly intuitive, approaches to data problems. As an alternative, I introduce the concept of using human-centered design principles and an iterative process to approach what you do with Big (and small) Data. As exemplars, I will walk-through a quick informal example and a real Datascope client project to highlight the flexibility and speed of these techniques.
Natural Language Processing: L01 introductionananth
This presentation introduces the course Natural Language Processing (NLP) by enumerating a number of applications, course positioning, challenges presented by Natural Language text and emerging approaches to topics like word representation.
Metaphic or the art of looking another way.Suresh Manian
For all intents and purposes, we are our words. And verbs and adjectives capture actions and sentiments better than any other tool. Metaphic is premised on the belief that a grammar book and a calculator are all you really need to make sense of web search and social media chatter, apart from all text, in general.
Mria Pia tackled the terminology trends and shared some interesting examples from her professional experience as a blogger:
1. Communicating about terminology by using social networks.
2. Social networks as available data for carrying out terminology research, in particular for monitoring language changes such as neologisms. More and more researchers are beginning to work on projects consisting in analyzing tweets to catch the next most popular word.
3. Websites are made of content and terminology is the critical part of the user experience.
4. Managing and sharing terminological data: cloud based, collaborative and social platforms.
5. The subject field of terminology is overwhelming, so some websites provide terminological resources in few clicks.
Marriage of speech, vision and natural language processingYaman Kumar
Speech generally is considered to have three parts to it: vision, aural, and the social construct. In recent years, although the field has been moving at a dramatic pace, progress is being made in silos. The primary reason for this being that speech is considered "spoken text" by practitioners and researchers alike. Most open-source datasets due to their distance from real-world conditions help in spreading this false impression. In this condition, it is not surprising that common and important features of speech like intonation and disfluency do not get captured by this intent. This tutorial aims to provide an appreciation of the "full-stack" of speech - aural, vision and the textual (or social construct) parts with a special emphasis on aspects that may have significance for current and future research.
Learn the steps to making your scientific, technical information easy to read and mobile search-friendly. Identify your audience and write web content that is easy to understand.
BrightonSEO 2019 - Mining the SERP for SEO, Content & Customer InsightsRory Truesdale
Find out how you can use Python to analyse the language of the SERPs for valuable insights on what your customers want and how this can be applied to improve the performance of your SEO campaign.
Surname 5Chang QiuLinguistic1112018Machine and Human.docxmabelf3
Surname 5
Chang Qiu
Linguistic
11/1/2018
Machine and Human Translate
Most of the contents in the article involve a lot of criticism of the activities and services of the google translate compared to the normal conversation done in a face to face communication. Douglas Hofstadter provides a definitive introduction into the modern uses of technology and its consequences and applications. It is a challenge for thinking technology will solve even the simplest of the forms of human existence, such as language and communication. Hofstadter considers Google translations does not have the capabilities of meeting the balance between human communication and the use of language in different contexts.
In the contemporary community, the field of language translation engines is experiencing a gradual improvement with the recent introduction of the deep neural nets. It has been suggested by some observers and professionals that the era of the “Great AI Awakening” is upon us. If such a development was to occur, it would cause a very devastating upheaval in the Douglas Hofstadter life and beliefs. Although he might be fascinated and interested in the concept of machines translators and the ability of machines to translate, he is still not interested in seeing the human translators being replaced by the inanimate machines.
The idea and belief that this might come, frightens him. To his belief, the concept of human translators should be given more credit and awareness mainly because he considers it to be a form of art which is derived from individuals with many years of language experience throughout their lifetime. If it were to occur that the human translators are to be replaced by the machine translators and become considered as past relics, Douglas Hofstadter would be very saddened and be left in a state of terrible confusion.
There are different issues highlighted by Hofstadter and these issues are at the inability to effectively translate human communication by a machine’s translation configurations. For example, one phenomenon provided in the translation of the statement "Dans Leur Maison, tout vient en paires. Il y a sa Voiture et sa voiture, ses serviettes et ses serviettes, sa bibliothèque et Les siennes” by the google translate. The translation fails due to the different acts and why it affects the consistency and credibility brought by the Google translation.
The translation of any language with the use of a machine translator also contains its own sets of misgivings and challenges. For example, in the case of the French translation, it has been noted that the conversion for French is one of the youngest enterprises as compared to the rest of the other translated language. However impressive the current progress of the endeavor has produced over the past couple of years, the language still continues to face several challenges and issues during their translation process. A recent examination was conducted, trying to identify the problems and c.
The presentation explains topics on study of language, applications on natural language processing, levels of language analysis, representation and understanding, linguistic background and elements of a simple noun phrase
Human quality raters have been the mainstay of search engine evaluation for decades but a sea-change is on its way due to the need for scale as machine learning and demand evolves.
Life of An SEO - Surfing The Waves of Googles Many Algorithmic UpdatesDawn Anderson MSc DigM
the life of an SEO is never boring. Search is always changing and subsequently Google's algorithms are updated to reflect changing search behaviours and to combat the actions of bad actors / spam in the search engine results pages. We look at past algorithms, the many types of algorithms and identify how you can ascertain whether you've been impacted by an algorithmic update and how to remedy / recover
Natural Semantic SEO - Surfacing Walnuts in Densely Represented, Every Increa...Dawn Anderson MSc DigM
Structured data accounts for only a small part of the web and the problem grows as the volume of the online content grows. Schema markup is a drop in the ocean to help with this. However, things are being addressed in the natural language research space in the form of dense retrieval and other developments such as Sentence BERT and FAISS. Utilising heuristics such as umbrellas and sidecar pages will help to send clues and assist with ensuring search engines rank the right pages from your sites for SEO
Whilst passage indexing may seem like a small tweak to search ranking, it is potentially much more symptomatic of the beginning of a fundamental shift in the way that search engines understand unstructured content, determine relevance in natural language, and rank efficiently and effectively.
It could also be a means of assessing overall quality of content and a means of dynamic index pruning. We will look at the landscape, and also provide some takeaways for brands and business owners looking to improve quality in unstructured content overall in this fast changing landscape.
Zipfs Law & Zipfian Distribution in SEO - Pubcon Virtual Fall 2020 - Dawn And...Dawn Anderson MSc DigM
Zipf's Law is prevalent throughout many forms of data and that includes the internet at large and within sectors of the internet, websites and web pages plus linguistics. How does this impact SEO if at all?
Disambiguating Equiprobability in SEO Dawn Anderson Friends of Search 2020Dawn Anderson MSc DigM
Connecting the probable dots in content and data can help significantly and improve your search strategy. Ambiguity in SEO comes in many form too, going beyond content and into entities and locations. This talk touches on some of the areas where ambiguity can impact and hinder your performance
Connecting The Worlds of Information Retrieval & SEO - Search solutions 2019 ...Dawn Anderson MSc DigM
The worlds of information retrieval and SEO are very connected and each benefits from the other as the amount of content and unstructured data on the web grows. Here I look at my experiences over the past few years of following both the IR and SEO worlds
It's very easy to get started too quickly in SEO for a new website and not plan properly using a framework to improve probability of success. Here we look at the SOSTAC framework for a new site and explore some traditional strategic models and marketing frameworks to employ in an SEO capacity for a dog friendly website in the UK territory. Expect SOSTAC, Porters 5 Forces, Ansoff Matrix, 5S's, 8P's and more
In an information economy where users are time poor and research hungry we need to take a mobile first approach to meet the needs of both users and search engines looking to align users informational needs with relevant search results. With limited space and a now mobile-first index how can we align our SEO strategy with this?
The changing search landscape calls for different approaches to user needs, including context, intent and device considerations. Here we take a look at ways to keep working to keep your ecommerce site well positioned for strong transactional and informational queries in the moments that matter to shoppers online.
Voice Search and Conversation Action Assistive Systems - Challenges & Opportu...Dawn Anderson MSc DigM
We are headed to the age of assistive task driven search where the user needs help to 'do' things as well as learn things. Smart speakers, mobile phones, assistive systems and conversational search and action devices are where the buck is headed for now. Where are we at in this wave? What are the challenges? What are the opportunities right now? Here we look at some of the ways we can start to prepare our tactics and strategy to be pioneering search marketers with conversation search and conversation action.
The Iceberg Approach - Power from what lies beneath in SEO for a mobile-first...Dawn Anderson MSc DigM
In a mobile-first world, with time-poor users, research crazy and mainly browsing with one eye and one hand, we need to consider a few new approaches to SEO. Information overload is all around. We need to think about how we can maintain relevance with less in some cases. We need to consider the Iceberg Theory and simultaneously consider the Iceberg Syndrome as well as placement position in user view for content and links
Mobile-first goes beyond simply indexing in a search engine. It has several meanings, which traverse user-behaviour, web design, adoption in different territories, adoption amongst user segments, adoption in different verticals. We need to be aware of these fundamentals changes in search behaviour and adapt quickly.
Here we take a look at server log file analysis for SEO and explore not only the benefits but also the process of finding, gathering, shipping and analysing user agent logs
Voice Search Challenges For Search and Information Retrieval and SEODawn Anderson MSc DigM
Whilst search engines are making great strides to achieve gold standards in error free voice search recognition there are still a number of challenges. We look at some of them here and seek to understand how we may adapt to optimise for them. Thanks to Enrique Alfonseca, the Google Conversational Research Team, ESSIR Barcelona for the great learnings and education.
A few of the recent findings we discovered whilst working on an SEO beast which cover crawling, server log file analysis, site speed optimization and database optimizations. Technical SEO insights
Cruft busting technical debt code smell and refactoring for seo - state of ...Dawn Anderson MSc DigM
Things can add up over time when you migrate sites or have many legacy domains, subdomains and old code in a website. Signs of poor quality add up as incremental crawling never stops. This is akin to SEO technical debt which you need to repay to regain good site health and positive quality signals. You can't repay the debt all at once, but in iterative incremental steps over time.
Duplicate content continues to confuse many of us. Part of the problem is there are different types of duplicate content which may be treated differently by search engines. There are different ways to deal with this in your SEO and content marketing strategy. It's important to be careful when removing content to ensure you're not shooting yourself in the foot. Instead of remove, try to improve or regroup content which is being triggered for the same query class / cluster and may be diluting. Change the emphasis and make something of added value for users. Consider query and category agnostic filtering versus content which is considered at query run-time auction in search results.
SEO - The Rise of Persona Modelled Intent Driven Contextual SearchDawn Anderson MSc DigM
Increasing volumes of data on users and 'users like users' via user modelling now provide search engines with clues as to what types of pages to rank for different user types, terms, in different contexts, locations & scenarios
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
The session includes a brief history of the evolution of search before diving into the roles technology, content, and links play in developing a powerful SEO strategy in a world of Generative AI and social search. Discover how to optimize for TikTok searches, Google's Gemini, and Search Generative Experience while developing a powerful arsenal of tools and templates to help maximize the effectiveness of your SEO initiatives.
Key Takeaways:
Understand how search engines work
Be able to find out where your users search
Know what is required for each discipline of SEO
Feel confident creating an SEO Plan
Confidently measure SEO performance
Digital Commerce Lecture for Advanced Digital & Social Media Strategy at UCLA...Valters Lauzums
E-commerce in 2024 is characterized by a dynamic blend of opportunities and significant challenges. Supply chain disruptions and inventory shortages are critical issues, leading to increased shipping delays and rising costs, which impact timely delivery and squeeze profit margins. Efficient logistics management is essential, yet it is often hampered by these external factors. Payment processing, while needing to ensure security and user convenience, grapples with preventing fraud and integrating diverse payment methods, adding another layer of complexity. Furthermore, fulfillment operations require a streamlined approach to handle volume spikes and maintain accuracy in order picking, packing, and shipping, all while meeting customers' heightened expectations for faster delivery times.
Amid these operational challenges, customer data has emerged as an important strategy. By focusing on personalization and enhancing customer experience from historical behavior, businesses can deliver improved website and brand experienced, better product recommendations, optimal promotions, and content to meet individual preferences. Better data analytics can also help in effectively creating marketing campaigns, improving customer retention, and driving product development and inventory management.
Innovative formats such as social commerce and live shopping are beginning to impact the digital commerce landscape, offering new ways to engage with customers and drive sales, and may provide opportunity for brands that have been priced out or seen a downturn with post-pandemic shopping behavior. Social commerce integrates shopping experiences directly into social media platforms, tapping into the massive user bases of these networks to increase reach and engagement. Live shopping, on the other hand, combines entertainment and real-time interaction, providing a dynamic platform for showcasing products and encouraging immediate purchases. These innovations not only enhance customer engagement but also provide valuable data for businesses to refine their strategies and deliver superior shopping experiences.
The e-commerce sector is evolving rapidly, and businesses that effectively manage operational challenges and implement innovative strategies are best positioned for long-term success.
Come learn how YOU can Animate and Illuminate the World with Generative AI's Explosive Power. Come sit in the driver's seat and learn to harness this great technology.
The digital marketing industry is changing faster than ever and those who don’t adapt with the times are losing market share. Where should marketers be focusing their efforts? What strategies are the experts seeing get the best results? Get up-to-speed with the latest industry insights, trends and predictions for the future in this panel discussion with some leading digital marketing experts.
Mastering Local SEO for Service Businesses in the AI Era is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
AI-Powered Personalization: Principles, Use Cases, and Its Impact on CROVWO
In today’s era of AI, personalization is more than just a trend—it’s a fundamental strategy that unlocks numerous opportunities.
When done effectively, personalization builds trust, loyalty, and satisfaction among your users—key factors for business success. However, relying solely on AI capabilities isn’t enough. You need to anchor your approach in solid principles, understand your users’ context, and master the art of persuasion.
Join us as Sarjak Patel and Naitry Saggu from 3rd Eye Consulting unveil a transformative framework. This approach seamlessly integrates your unique context, consumer insights, and conversion goals, paving the way for unparalleled success in personalization.
Top 3 Ways to Align Sales and Marketing Teams for Rapid GrowthDemandbase
In this session, Demandbase’s Stephanie Quinn, Sr. Director of Integrated and Digital Marketing, Devin Rosenberg, Director of Sales, and Kevin Rooney, Senior Director of Sales Development will share how sales and marketing shapes their day-to-day and what key areas are needed for true alignment.
Digital Money Maker Club – von Gunnar Kessler digital.focsh890
Title One is a comprehensive examination of the impact of digital technologies on
modern society. In a world where technology continues to advance rapidly, this article delves into the nuances and complexities of the digital age, exploring Its implications across various sectors and aspects of life.
Financial curveballs sent many American families reeling in 2023. Household budgets were squeezed by rising interest rates, surging prices on everyday goods, and a stagnating housing market. Consumers were feeling strapped. That sentiment, however, appears to be waning. The question is, to what extent?
To take the pulse of consumers’ feelings about their financial well-being ahead of a highly anticipated election, ThinkNow conducted a nationally representative quantitative survey. The survey highlights consumers’ hopes and anxieties as we move into 2024. Let's unpack the key findings to gain insights about where we stand.
Search Engine Marketing - Competitor and Keyword researchETMARK ACADEMY
Over 2 Trillion searches are made per day in Google search, which means there are more than 2 Trillion visits happening across the websites of the world wide web.
People search various questions, phrases or words. But some words and phrases are searched
more often than others.
For example, the words, ‘running shoes’ are searched more often than ‘best road running
shoes for men’
These words or phrases which people use to search on Google are called Keywords.
Some keywords are searched more often than others. Number of times a keyword is searched
for in a month is called keyword volume.
Some keywords have more relevant results than others. For the phrase “running shoes” we
get more than 80M relevant results, whereas for “best road running shoes for men” we get
only 8.
The former keyword ‘running shoes’ has way more competition from popular websites to
new and small blogs, whereas the latter keyword doesn’t have that much competition. This
search competition for a keyword is called search difficulty of a keyword or keyword
difficulty.
In other words, if the keyword difficulty is ‘low’ or ‘easy’, there won’t be any competition
and if you target such keywords on your site, you can easily rank on the front page of Google.
Some keywords are searched for, just to know or to learn some information about something,
that’s their search intention. For example, “What shoe size should I choose?” or “How to pick
the right shoe size?”
These keywords which are searched just to know about stuff are called informational
keywords. Typically people who are searching this type of keywords are top of a Conversion
funnel.
Conversion funnel is the journey that search visitors go through on their way to an email
subscription or a premium subscription to the services you offer or a purchase of products
you sell or recommend using your referral link.
For some buyers, research is the most important part when they have to buy a product.
Depending on that, their journey either widens or narrows down. These types of buyers are
Researchers and they spend more time with informational keywords.
Conversion is the action you want from your search visitors. Number of conversions that you
get for every 100 search visitors is called Conversion rate.
People who are at different stages of a conversion funnel use different types of keywords.
Monthly Social Media News Update May 2024Andy Lambert
TL;DR. These are the three themes that stood out to us over the course of last month.
1️⃣ Social media is becoming increasingly significant for brand discovery. Marketers are now understanding the impact of social and budgets are shifting accordingly.
2️⃣ Instagram’s new algorithm and latest guidance will help us maintain organic growth. Instagram continues to evolve, but Reels remains the most crucial tool for growth.
3️⃣ Collaboration will help us unlock growth. Who we work with will define how fast we grow. Meta continues to evolve their Creator Marketplace and now TikTok are beginning to push ‘collabs’ more too.
A.I. (artificial intelligence) platforms are popping up all the time, and many of them can and should be used to help grow your brand, increase your sales and decrease your marketing costs.In this presentation:We will review some of the best AI platforms that are available for you to use.We will interact with some of the platforms in real-time, so attendees can see how they work.We will also look at some current brands that are using AI to help them create marketing messages, saving them time and money in the process. Lastly, we will discuss the pros and cons of using AI in marketing & branding and have a lively conversation that includes comments from the audience.
Key Takeaways:
Attendees will learn about LLM platforms, like ChatGPT, and how they work, with preset examples and real time interactions with the platform. Attendees will learn about other AI platforms that are creating graphic design elements at the push of a button...pre-set examples and real-time interactions.Attendees will discuss the pros & cons of AI in marketing + branding and share their perspectives with one another. Attendees will learn about the cost savings and the time savings associated with using AI, should they choose to.
Unleash the power of UK SEO with Brand Highlighters! Our guide delves into the unique search landscape of Britain, equipping you with targeted strategies to dominate UK search engine results. Discover local SEO tactics, keyword magic for UK audiences, and mobile optimization secrets. Get your website seen by the right people and propel your brand to the top of UK searches.
To learn more: https://brandhighlighters.co.uk/blog/top-seo-agencies-uk/
In this presentation, Danny Leibrandt explains the impact of AI on SEO and what Google has been doing about it. Learn how to take your SEO game to the next level and win over Google with his new strategy anyone can use. Get actionable steps to rank your name, your business, and your clients on Google - the right way.
Key Takeaways:
1. Real content is king
2. Find ways to show EEAT
3. Repurpose across all platforms
3. @dawnieando
• A Google algorithmic
update
• Google announce BERT to the
organic search world in a VERY
geeky way
• Mentions of the 15% of new
queries every day
• Touches on ‘The Vocabulary
Problem’ (many ways of querying
the same thing)
October 2019 - Welcome To Search, BERT
4. @dawnieando
• Probably the biggest
improvement in search EVER
• The biggest change in search
in five years, since RankBrain
Fundamentally… Google BERT is
5. @dawnieando
!Layman’s Terms: it can be
used to help Google better
understand the context of
words in search queries &
content
So, just what is Google BERT update?
6. @dawnieando
• Used globally in all
languages on featured
snippets
• BERT to impact rankings for 1
in 10 queries
• Initially for English language
queries in US
The bottom line search announcement
7. @dawnieando
Dec 2019 – BERT expands internationally
• Over 70 languages
• Still only impacts 10% of
queries despite the
considerable expansion
• Still all featured snippets
globally
8. @dawnieando
• BERT deals with
ambiguity & ‘nuance’ in
queries & content
• Unlikely to impact short
queries
• More likely to impact
conversational queries
• Unlikely to impact
branded queries
Why just 10% of Google Queries Impacted?
9. @dawnieando
• The SEO community is
abuzz
• BERT is a big deal
• Likened to ‘Rank Brain’ in
some of the ‘interesting’
interpretations
• Some confusions around
‘What BERT is and what it
means for search’
SEO’s React
10. @dawnieando
!A neural network-based
technique for natural language
processing pre-training
!An anagram of Bi-Directional
Encoder Representations from
Transformers
BERT in Geek Speak
12. @dawnieando
• Search algorithm update
• Open source pre-trained model / framework for
natural language understanding
• Academic research paper
• Evolving tool for computational linguistics efficiency
• Beginning of MANY BERT’ish language models
Important: BERT is Many Things
13. @dawnieando
So What’s The Backstory?
Where%did%BERT%come%from?
Where%did%the%need%for%BERT%arise?
The$Impact$of$BERT$for$SEO$&$beyond?
What%next?
14. @dawnieando
• Academic Paper
• Research Project by Devlin et al
• Published a year before the
update in October 2018
• Bert: Pre-training of deep
bidirectional transformers for
language understanding
BERT started as a research paper in 2018
15. @dawnieando
• Open sourced so anyone can
build a BERT
• BERT created a sea-change
leap-forward in natural language
understanding in information
retrieval very quickly
• Provided a pre-trained language
model which required only fine-
tuning
BERT Open Sourced in 2018
16. @dawnieando
The whole of the English
Wikipedia & The Books
Corpus combined.
Over 2,500 million words
BERT Has Been Pre-Trained On Many Words
17. @dawnieando
Vanilla BERT provides a pre-
trained starting point layer for
neural networks in machine
learning & natural language
diverse tasks
The machine learning community got very
excited about BERT
18. @dawnieando
• BERT is fine-tuned on a variety of
downstream NLP tasks, including
question and answer datasets
BERT Can Be Fine-Tuned in A Short Space of Time
19. @dawnieando
• Vanilla BERT can be used ‘out of the box’
or fine-tuned
• Provides a great starting point & saves
huge amounts of time & money
• Those wishing to, ‘can build upon’, and
improve BERT
BERT Saves Researchers Time AND Money
20. @dawnieando
• Microsoft – MT-DNN
• Facebook – RoBERTa
• XLNet
• ERNIE – Baidu
• Lots of other
contenders
Since 2018 Major tech companies extend BERT
25. @dawnieando
Language models like
BERT help machines
understand the nuance
in word’s context and
surrounding text
cohesion
What Purpose Does BERT Serve & How?
26. @dawnieando
• Dates back over 60 years old to the Turing Test paper
• Aims at understanding the way words fit together with
structure and meaning.
• NLU is Connected to the field of linguistics (computational
linguistics)
• Over time, increasingly computational linguistics
overflows to a growing online web of content
What is Natural Language Understanding?
30. @dawnieando
“The meaning of a word is its use in a
language” (Ludwig, Wittgenstein,
Philosopher, 1953)
Image attribution: Mortiz, Nahr
(Public domain)
Single Words Have No Meaning
31. @dawnieando
The word ‘like’ in this sentence, is both a:
!(VBP) : (‘verb’ (non 3rd-person, singular,
present) )
!(IN) : (Preposition or subordinating
conjunction)
An Example of Word’s Meaning Changing
• I -> PRP
• Like -> VBP
• That -> IN
• He -> PRP
• Is -> VBZ
• Like -> IN
• That -> DT
33. @dawnieando
E.g. Verbs, nouns, adjectives
• Penn-treebank tagger -> 36
different parts of speech
• CLAWS7 (C7) -> 146 different
parts of speech
• Brown Corpus Tagger -> 81
different parts of speech
Words Are ‘Part of Speech’ When Combined
34. @dawnieando
• He kicked the bucket
• I have yet to tick that off
my bucket list
• The bucket was filled with
water
The Meaning of The Word ‘Bucket’ Changes
35. @dawnieando
Words Need ’Text Cohesion’
The$‘Glue’$which$adds$meaning
May$historically$be$‘stop$words’
Surrounding)words)can)change)‘intent’
They%add%‘context’
36. @dawnieando
”Ambiguity is the greatest bottleneck to computational
knowledge acquisition, the killer problem of all natural
language processing.”
(Stephen Clark, formerly of Cambridge University & now a full-
time research scientist with Google Deep Mind)
Ambiguity Is Problematic
37. @dawnieando
• Words with a similar meaning to something else
• Example: humorous, comical, hilarious, hysterical are ALL
synonyms of funny
Synonymous (Synonyms)
38. @dawnieando
Ambiguity & Polysemy
• Ambiguity is at a sentence level
• Polysemous words are arguably the
most problematic due to ‘nuanced’
nature
39. @dawnieando
• Words usually with the
same root and multiple
meanings
• Example: “Run” has 396
Oxford English Dictionary
definitions
Polysemous (Polysemy)
41. @dawnieando
• Words spelt the same but with very different ‘root’ of word
meanings
• Example: pen (writing implement), pen (pig pen)
• Example: rose (stood up / ascended), rose (flower)
• Example: bark (dog sound), bark (tree bark)
Homonyms
42. @dawnieando
Spelt differently with
VERY different
meanings but
sound exactly the
same
• Draft, draught
• Dual, duel
• Made, maid
• For, fore, four
• To, too, two
• There, their
• Where, wear, were
Homophones – Difficult To Disambiguate Verbally
46. @dawnieando
EXAMPLES
• Zipfian Distribution
• Firthian Linguistics
• Treebanks
• Language can be tied back to
mathematical spaces & algorithms
Language Has Natural Patterns & Phenomena
47. @dawnieando
Example: Zipfian Distribution (Power Law)
• The frequency of any
word in a collection is
inversely proportional to
its rank in the frequency
table
• Applies to any word
frequency ANYWHERE
• Image is 30 Wikipedias
48. @dawnieando
To illustrate Zipfian Distribution (Most used Words):
Rank Word Frequency)of)Use)in)a)Corpus
1 the
2 be 1/2
3 to 1/3
4 of 1/4
5 and 1/5
6 a 1/6
7 in 1/7
8 that 1/8
9 have 1/9
10 I 1/10
49. @dawnieando
“You shall know a word by the
company it keeps” (Firth, 1957)
Firthian Linguistics
One Such Phenomenon is Co-occurrence
50. @dawnieando
Words with similar meaning tend
to live near each other in a body
of text
Word’s ‘nearness’ can be
measured in mathematical vector
spaces – a context vector is
‘word’s company’
Distributional Relatedness & Firthian Linguistics
51. @dawnieando
Co-occurrence, Similarity & Relatedness
• Language models
are trained on
large bodies of
text to learn
‘distributional
similarity’ (co-
occurrence)
52. @dawnieando
Context Vectors & Word Embeddings
• And build vector
space models for word
embeddings
• Models learn the
weights of similarity &
relatedness distances
54. @dawnieando
• He kicked the bucket
• I have yet to tick that off
my bucket list
• The bucket was filled with
water
Remember ‘bucket’ Without Text Cohesion?
55. @dawnieando
Word’s Context Still Needed Gaps Filling
• Past models used
context-free
embeddings
• A moving
‘context window’
was used to gain
word’s context
56. @dawnieando
But Even Then True Context Needs Both Sides of a
Word
• Past models were
‘uni-directional’
• The context
window moved
from left to right
or right to left
61. @dawnieando
!Transformer is a big
deal
!Derived from a 2017
paper called ‘Attention
is all you Need’ (Vaswani, A.,
Shazeer, N., Parmar, N., Uszkoreit, J., Jones,
L., Gomez, A.N., Kaiser, Ł. and Polosukhin,
I., 2017)
What About The Transformer Part?
64. @dawnieando
River Bank or Financial Bank?
By identifying ‘cheque’ or
‘deposit’ in the company
of ‘bank’ BERT can
disambiguate from a ‘river’
bank
65. @dawnieando
So Where is BERT’s Value in Google Search
• Named entity determination
• Textual entailment (next sentence prediction)
• Coreference resolution
• Question answering
• Word sense disambiguation
• Automatic summarization
• Polysemy resolution
68. @dawnieando
!A single word can change the whole intent of a query
!Conversational queries particularly so
!The ‘stop words’ are actually part of text-cohesion
!Historically ‘stop-words’ were often ignored
!The next sentence matters
BERT and Intent Understanding
69. @dawnieando
Example:
“I remember what my
Grandad said just
before he kicked the
bucket.”
Next Sentence Prediction (Textual Entailment)
Often the next sentence REALLY matters
71. @dawnieando
• There have been lots of improvement by others upon
BERT
• Google have likely improved dramatically on BERT too
• There were some issues with next-sentence prediction
• Facebook built RoBERTa
BERT Probably Doesn’t Resemble The Original BERT
Paper
72. @dawnieando
• Named entity determination
• Coreference resolution
• Question answering
• Word sense disambiguation
• Automatic summarization
• Polysemy resolution
Featured Snippets
Knowledge Graph & Web Page Extraction
Together
73. @dawnieando
!BERT is multilingual from mono-lingual
!Other language specific BERTs are being built
!Transformer was trained on international translations
!Language has transferrable phenomena
BERT and International SEO
Expect Big Things
74. @dawnieando
• Deepset – German BERT
• CamemBERT – French BERT
• AlBERTo – Italian BERT
• RobBERT - Dutch RoBERTa model
BERT & International SEO
75. @dawnieando
!The challenges of Pygmalion
!Conversational search can now ‘scale’
!BERT takes away some of the human
labelling effort necessary
!Next sentence prediction could impact
assistants and clarifying questions
BERT and Conversational Search
Expect Big Things
76. @dawnieando
Semantic Heterogeneity Issues in Entity Oriented
Search (Semantic Search)
!Helps with anaphora & cataphora
resolution (resolving pronouns of entities)
!Helps with coreference resolution
!Helps with named entity determination
!Next sentence prediction could impact
assistants and clarifying questions
78. @dawnieando
• It’s supposed to be natural
• In the same way you can’t optimize for Rank
Brain you can’t optimize for BERT
• BERT is a tool / learning process in search for
disambiguation & contextual understanding of
words
• BERT is a ‘black-box’ algorithm
Why can’t you optimize for BERT?
79. @dawnieando
• Black-box algorithm
• Hugging Face coined the phrase
BERTology
• Now a field of study exploring why
BERT makes choices
• Some concerns over bias &
responsible AI
Black Box Algorithms & BERTology
80. @dawnieando
!Cluster together content and interlink well on topic & nuance
!Avoid ‘too-similar’ completing categories - merge
!Consider not just the content in the page but the content in
the linked pages & sections
!Consider the content of the ‘whole domain’ as everything
contributes in co-occurrence
!Be extra vigilant when ‘pruning
Utilising Co-Occurrence Strategically
Employ Relatedness
82. @dawnieando
Anyone can build a BERT to train their own
language processing system for a variety of
natural language understanding downstream
tasks.
Fine-tuning can be carried out in a short time
BERT represents a union of data science and SEO
Anyone Can Use BERT – BERT is a Tool
83. @dawnieando
• Automatic categorization & subcategorization of
content
• Automatic generation of meta-descriptions
• Automatic summarization of extracts & teasers
• Categorising user-generated content / posts
probably better than humans
How Could BERT Be Harnessed For Efficiency
in SEO? A Few Examples
84. @dawnieando
• J R Oakes - @jroakes
• Hamlet Batista - @hamletbatista
• Andrea Volpini - @cyberandy
• Gefen Hermesh - @ghermesh
SEOs Are Getting Busy With BERTishness
86. @dawnieando
• Original BERT was computationally expensive to
run
• ALBERT stands for A Lite BERT
• Increased efficiency
• ALBERT is BERT’s natural successor
• ALBERT much leaner whilst providing similar
results
• A joint research work between Google & Toyota
ALBERT – BERT’s Successor
87. @dawnieando
Reformer (Google) – Transformer’s Successor
Understands word’s context
from the perspective of a
‘whole novel’.
https://venturebeat.com/2020/01/16/goog
les-ai-language-model-reformer-can-
process-the-entirety-of-novels/
88. @dawnieando
Growth has been huge in the natural language
processing community – Current Superglue
Leaderboard
BERT Was Just The Start
• Google T5 is winning
• Even more
advanced
technology
• Transfer-learning
• Expect big things