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.
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
Search Query Processing: The Secret Life of Queries, Parsing, Rewriting & SEOKoray Tugberk GUBUR
Query Processing is the process of query term weight calculation, query augmentation, query context defining, and more. Query understanding and Query clustering are related to Information Retrieval tasks for the search engines. To provide a better search engine optimization effort and project result, the organic search performance optimizers need to implement query processing methodologies. Digital marketing and SEO are connected to each other. Understanding a query includes query parsing, query rewriting, question generation, and answer pairing. Multi-stages Query Processing, Candidate Answer Passages, or Candidate Answer Passages and Answer Term Weighting are some of the concepts from the Google Search Engine to parse the queries.
The presentation of The Secret Life of Queries, Parsing, Rewriting & SEO has been presented at the Brighton SEO Event in April 2022. The event speech focused on explaining the theoretical SEO and practical SEO examples together.
Query Processing methodologies are beyond synonym matching or synonym finding. It involves multiple aspects of the words, and meanings of the words. The theme of words, the centrality of words, attention windows, context windows, and word co-occurrence matrices, GloVe, Word2Vec, word embeddings, character embeddings, and more.
Themes of words contain the word probability like in Continues Bag of Window.
The search engine optimization community focuses on keyword research by matching the queries. Query processing involves query word order change, query word type change, query word combination change, query phrase synonym usage, query question generation, query clustering. Query processing and document processing are correlational. Query processing is to understand a query while document processing is to process a web document. Both of the processes are for ranking algorithms. Providing a better ranking algorithm requires a better query understanding. And providing better rankings as SEOs require better search engine understanding. Thus, understanding the methods of query processing is necessary.
Search Query Processing is implementing the query processing for thesearch engines. Search query refers to the phrase that search engine users use for searching. Search intent understanding and search intent grouping are two different things. But, query templates, questions templates, and document templates work together. Search query is for organic search behaviors. A web search engine answers millions of queries every day. Search query processing is a fundamental task for search engine optimization and search engine result page optimization.
The "Semantic Search Engine: Query Processing" slides from Koray Tuğberk GÜBÜR supported the presentation of "Search Query Processing: The Secret Life of Queries, Parsing, Rewriting & SEO". The presentation has been created by Dear Rebecca Berbel.
Many thanks to the Google engineers that created the Semantic Search Engine patents including Larry Page.
Technical SEO Myths Facts And Theories On Crawl Budget And The Importance Of ...Dawn Anderson MSc DigM
There are a lot of myths, facts and theories on crawl budget and the term is bandied around a lot. This deck looks to address some of those myths and also looks at some additional theories around the concepts of 'crawl rank' and 'search engine embarrassment'.
Building a semantic search system - one that can correctly parse and interpret end-user intent and return the ideal results for users’ queries - is not an easy task. It requires semantically parsing the terms, phrases, and structure within queries, disambiguating polysemous terms, correcting misspellings, expanding to conceptually synonymous or related concepts, and rewriting queries in a way that maps the correct interpretation of each end user’s query into the ideal representation of features and weights that will return the best results for that user. Not only that, but the above must often be done within the confines of a very specific domain - ripe with its own jargon and linguistic and conceptual nuances.
This talk will walk through the anatomy of a semantic search system and how each of the pieces described above fit together to deliver a final solution. We'll leverage several recently-released capabilities in Apache Solr (the Semantic Knowledge Graph, Solr Text Tagger, Statistical Phrase Identifier) and Lucidworks Fusion (query log mining, misspelling job, word2vec job, query pipelines, relevancy experiment backtesting) to show you an end-to-end working Semantic Search system that can automatically learn the nuances of any domain and deliver a substantially more relevant search experience.
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.
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
Search Query Processing: The Secret Life of Queries, Parsing, Rewriting & SEOKoray Tugberk GUBUR
Query Processing is the process of query term weight calculation, query augmentation, query context defining, and more. Query understanding and Query clustering are related to Information Retrieval tasks for the search engines. To provide a better search engine optimization effort and project result, the organic search performance optimizers need to implement query processing methodologies. Digital marketing and SEO are connected to each other. Understanding a query includes query parsing, query rewriting, question generation, and answer pairing. Multi-stages Query Processing, Candidate Answer Passages, or Candidate Answer Passages and Answer Term Weighting are some of the concepts from the Google Search Engine to parse the queries.
The presentation of The Secret Life of Queries, Parsing, Rewriting & SEO has been presented at the Brighton SEO Event in April 2022. The event speech focused on explaining the theoretical SEO and practical SEO examples together.
Query Processing methodologies are beyond synonym matching or synonym finding. It involves multiple aspects of the words, and meanings of the words. The theme of words, the centrality of words, attention windows, context windows, and word co-occurrence matrices, GloVe, Word2Vec, word embeddings, character embeddings, and more.
Themes of words contain the word probability like in Continues Bag of Window.
The search engine optimization community focuses on keyword research by matching the queries. Query processing involves query word order change, query word type change, query word combination change, query phrase synonym usage, query question generation, query clustering. Query processing and document processing are correlational. Query processing is to understand a query while document processing is to process a web document. Both of the processes are for ranking algorithms. Providing a better ranking algorithm requires a better query understanding. And providing better rankings as SEOs require better search engine understanding. Thus, understanding the methods of query processing is necessary.
Search Query Processing is implementing the query processing for thesearch engines. Search query refers to the phrase that search engine users use for searching. Search intent understanding and search intent grouping are two different things. But, query templates, questions templates, and document templates work together. Search query is for organic search behaviors. A web search engine answers millions of queries every day. Search query processing is a fundamental task for search engine optimization and search engine result page optimization.
The "Semantic Search Engine: Query Processing" slides from Koray Tuğberk GÜBÜR supported the presentation of "Search Query Processing: The Secret Life of Queries, Parsing, Rewriting & SEO". The presentation has been created by Dear Rebecca Berbel.
Many thanks to the Google engineers that created the Semantic Search Engine patents including Larry Page.
Technical SEO Myths Facts And Theories On Crawl Budget And The Importance Of ...Dawn Anderson MSc DigM
There are a lot of myths, facts and theories on crawl budget and the term is bandied around a lot. This deck looks to address some of those myths and also looks at some additional theories around the concepts of 'crawl rank' and 'search engine embarrassment'.
Building a semantic search system - one that can correctly parse and interpret end-user intent and return the ideal results for users’ queries - is not an easy task. It requires semantically parsing the terms, phrases, and structure within queries, disambiguating polysemous terms, correcting misspellings, expanding to conceptually synonymous or related concepts, and rewriting queries in a way that maps the correct interpretation of each end user’s query into the ideal representation of features and weights that will return the best results for that user. Not only that, but the above must often be done within the confines of a very specific domain - ripe with its own jargon and linguistic and conceptual nuances.
This talk will walk through the anatomy of a semantic search system and how each of the pieces described above fit together to deliver a final solution. We'll leverage several recently-released capabilities in Apache Solr (the Semantic Knowledge Graph, Solr Text Tagger, Statistical Phrase Identifier) and Lucidworks Fusion (query log mining, misspelling job, word2vec job, query pipelines, relevancy experiment backtesting) to show you an end-to-end working Semantic Search system that can automatically learn the nuances of any domain and deliver a substantially more relevant search experience.
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.
SEO Başarı Hikayesi - Hangikredi.com 12 Mart'tan 24 Eylül Google Core Güncell...Koray Tugberk GUBUR
Özeti Başlat:
"5 Ayda% 131 Organik Oturum Artışı
5 Ay İçinde% 62 Gösterim Artışı
5 Aylık% 144 Tıklama Artışı "
Bu SEO Vaka çalışması, Google Çekirdek Güncellemeleri ve Türkiye'deki en büyük finansal kurum web sitesine etkileri ile ilgili.
Hangikredi.com'da 26 Mart 2019'da çalışmaya başladım. Ancak şirketin web sitesi 12 Mart Google Çekirdek Güncellemesi'nden çok olumsuz etkilendi.
Bir kriz yaşanırken burada çalışmaya başladım.
Web sitesini inceledim ve asıl sorunların tarama bütçesi, otorite işareti ve alaka düzeyi-işletme ilişkisi olduğunu anladım. Sosyal medyayı, Google İş Hesaplarım'ı etkinleştirdim, diğer tüm alternatif kanallardan finansal forumlara girdim. Bizimle ilgili bir haber yayıncı ağı yarattım. Yanıltıcı durum kodlarını, HTML ve CSS hatalarını temizledim, meta etiketleri optimize ettim, yönlendirme zincirlerini düzelttim, görüntü sıkıştırma kullandım ve birçok gereksiz URL ve içeriğini sildim, iç bağlantı yapısını sıfırdan yarattım.
5 Haziran’dan Google Çekirdek Güncelleme’ye kadar tekrar kazandık.
Kaybettiğimiz bütün trafiğimizi geri kazandık. 1 Ağustos sunucu atack kadar, biz iyiydik, sonra bir gün, her şey ters gitti.
Yine 0'dan başladım ...
Web sitemizin offpage sinyallerini Google AI’ın güvenini yeniden kazanmak için optimize ediyordum ve bu stratejiyi onpage öğeleriyle destekliyordum.
24 Eylül Google Çekirdek Güncellemesi’nden sonra başka bir başarı daha oldu. Tarama yükü / oranı kaydını, ortalama site konumunu, TO'yu ve gösterimini, site geçmişi için tıklama kayıtlarını kırdık.
Bu CASE Çalışmasında grafikler içeren bir SEO Başarı Hikayesinin ayrıntılarını ve hayatımdaki bazı komik cencor resimlerini bulacaksınız.
Bitiş Özeti:
"12 Mart, 5 Haziran ve 24 Eylül 1 Ağustos Sunucu ile Google Çekirdek Güncellemeleri Atack, bu SEO Casse Çalışmasının kilometre taşlarıdır. Tüm detayları bizim açımızdan göreceksiniz. Umarım beğenirsiniz."
SGE, New Features in Google Search & How to Respond.pdfLily Ray
Lily Ray presented at the 2023 Engage PDX conference in Portland, Oregon about Google's Search Generative Experience (SGE), how it works, and concerns about SGE and its impact on SEO.
Different types of graphs and when you should use each + some random visuals I've always found useful.
Patrick Stox presenting at Digital Elite Day 2020
Semantic Search Engine: Semantic Search and Query Parsing with Phrases and En...Koray Tugberk GUBUR
Semantic Search Engines can understand human language to analyze the need behind a query. Instead of focusing, string, or word matching, a semantic search engine focuses on concepts, intents, and relations of named entities. Taxonomy, ontology, onomastics, semantic role labeling, relation detection, lexical semantics, entity extraction, recognition, resolution can be used by semantic search engines. In this PDF file, semantic search engines' evolution will be processed based on Google Search Engine's research papers, patents, and official announcements. From 1998 to 20021, search's and search engines' evolution, from strings to things, from phrases to entities will be told along with query processing, and parsing methodology changes.
As opposed to lexical search, semantic searching searches for meaning, not meaningless matches of the query words. Semantic search attempts to increase the relevancy of results by understanding searchers' intents and the context of terms in the searchable dataspace, whether online or within a closed system. The right semantic search content is a blend of natural language, focuses on the intent of the user, and considers other topics the user may be interested in.
Ontologies, XML, and other structured data sources can be used to retrieve knowledge using semantic search according to some authors. The use of such technologies provides a mechanism for creating formal expressions of domain knowledge that are highly expressive and may allow the user to express more detailed intent during query processing.
BrightonSEO March 2021 | Dan Taylor, Image Entity TagsDan Taylor
My talk from BrightonSEO 2021; focusing on using Google's image category labels (glancing into the Knowledge Graph and Google's image annotation processes) for better topic research and content optimization.
The Python Cheat Sheet for the Busy MarketerHamlet Batista
What percentage of an Inbound marketer's day doesn't involve working with spreadsheets? How much of this work is time-consuming and repetitive? In this interactive session, you will learn how to manipulate Google Sheets to automate common data analysis workflows using Python, a very easy to use programming language.
Understanding Semantic Search and AI Content to Drive Growth in 2023 March 2023TysonStockton1
Exploring modern search engines, semantic search, and AI technology to better understand how we can integrate into SEO strategy and content initiatives.
With the rise of ChatGPT there has been a lot of discussion around if SEO content is good or bad. To best determine how to leverage this technology in SEO workflows we must revisit how a modern search engine works and where we are at with AI technology.
Topics Covered:
1. Intro (Speaker, LLM, Will AI replace you)
2. AI for SEO
3. Understanding Prompts
4. How we @Botpresso Use AI (Python Scripts & Case Study)
5. DOs & DONTs
6. Tools
7. 10 Commandments
8. AI-driven Prompt Mastery 🎁
AI Prompts for SEO E-book: https://botpresso.com/ai-prompts-for-seo/
Crawling, indexation & the impact on performance | Brighton SEOMartin Sean Fennon
Brighton SEO presentation given by Martin Fennon, the Head of SEO for Ayima. This talk covers crawling, indexation & the tangible impact reviewing these elements can have on performance
Lexical Semantics, Semantic Similarity and Relevance for SEOKoray Tugberk GUBUR
Lexical semantics and relations between words include relations of superiority, inferiority, part, whole, opposition, and sameness between the meanings of words. The same word can be a meronymy, hyponym, or antonym of another word, depending on the word before or after it. The lexical relation value of the first word can affect the structure of the next word, affecting the context of the sentence and the Information Retrieval Score. Information Retrieval Score is the score that determines how much content is related to a query, how close the different variants of the related query are, and the structure processed by the search engine’s query processor to the relevant document. A higher information retrieval score represents better relevance and possible click satisfaction.
The problem with a semi-structured and distracting context for Information Retrieval Score is that, if a document is not configured for a single topic, the IR Score can be diluted by the two different contexts resulting in a relative rank lost to another textual document.
IR Score Dilution involves badly structured lexical relations, along with bad word proximity. The relevant words that complete each other within the meaning map should be used closely, within a paragraph or section of the document, to signal the context in a more clear way to increase the IR Score. A search engine can check whether the document contains the hyponym of the words within the query or not. A possible query prediction can be generated from the hypernyms of the query. A search engine can check only the anchor texts to see whether there is a word within the “hyponym distance” which represents the hyponym depth between two different words.
Lexical Relations can represent the semantic annotations for a document. A semantic annotation is a word that describes the document overall in terms of category and main context that carries the purpose of the document. A semantic annotation can contain the main entity of the document or a general concept for covering a broader meaning area (knowledge domain). Semantic Annotations can be generated with the lexical relations between words. A semantic annotation can be used to match the document to the query. Semantic annotations are factors for a better IR Score.
A search engine can generate phrase patterns from the lexical relationships between words within the queries or the documents. A phrase pattern contains sections that define a concept with qualifiers. Phrase patterns can contain a hyponym just after an adjective, or a hypernym with the antonym of the same adjective. Most of these connections and patterns are used within the Recurrent Neural Network (RNN) for the next word prediction. A phrase pattern helps a search engine to increase its confidence score for relating the document to the specific query, or the meaning of the query.
Coronavirus and Future of SEO: Digital Marketing and Remote CultureKoray Tugberk GUBUR
I have attended a great SEO and Digital Marketing webinar with Founder of Stradiji and SEMRush Turkey Lead Mr. Mert Erkal and My Dearest Friend and SEO Consultant Atakan Erdoğan.
Small Note: After I uploaded the presentation, Google launched a new Covid-19 news address like Bing/covid-19. You may want to look at it -> https://www.google.com/covid-19
I have prepared a Presentation about Coronavirus's Effects on Search Engine Optimization (SEO).
You will find Coronavirus's changing effects on Digital Marketing and psychology of global society while using Search Engines.
I also have focused on Search Engine's and Social Media Brands, E-commerce Site's reflexes against Coronavirus Pandemic.
You will see the web sites and categories who earn more traffic and lose traffic. You will also see conversion rate differences because of Coronavirus.
Also, I have told about Search Engine's differences and their attitude against the Coronavirus Pandemic, their future, their updates during the pandemic.
In the last part, you will see some new 2020 Web Technology and Design Trends with AI.
There are also Google Researches for better Search Engine technologies.
Questions:
1- What are the differences between Yandex, Google, Bing, and Duckduckgo for Coronavirus Pandemic?
2- Twitter, Instagram, Amazon or Apple, what are they doing?
3- What do people search most for during the Coronavirus Crisis?
4- What changes from country to country?
5- What are the future technologies of Web and App?
6- How and why do Search Engines improve AI, what is the last events?
7- Which sites loose traffic and which earn more?
8- Lots of quotes from International SEOs about the pandemic.
And more...
I am Koray Tuğberk GÜBÜR and a Holistic SEO Expert.
I sincerely thank you for my Dearest Friend Atakan Erdoğan and Mr. Mert Erkal for this awesome webinar opportunity and experience.
To watch the webinar, please visit Stradiji's Official Youtube Channel.
https://www.youtube.com/watch?v=V4sJTNcRqaM&t=100s
Opinion-based Article Ranking for Information Retrieval Systems: Factoids and...Koray Tugberk GUBUR
How Search Engines Leverage Opinion-based Articles for Ranking?
Search engines use opinions, and factoids to understand the consensus. News search engines use different reports, and opinions in their search results to satisfy the urgent news information needed by the newsreaders. The news search engines differentiate disinformation from information to protect the newsreaders. Google, Microsoft Bing, Yandex, and DuckDuckGo have different algorithms and prioritization for classifications of the news sources, or prioritization of the news, and newsworthy topics.
Corroboration of the Web Answers from the Open Web is a research paper from Amelia Marian and Minji Wu explaining how a search engine can rank information according to its accuracy.
Google started to explain that the Expertise-Authoriteveness-Trustworthiness is the most important group of signals to be sure that a result won't shame the search engine. Embarrassment factors for the search engines involve wrong information on a news title on the news story, or a wrong featured snippet. A search engine might be shame due to the bad result that is ranking on the SERP.
Dense-retrieval, context scoring, named entity recognition, semantic role labeling, truth ranges, fix points, confidence score, query processing, and parsing.
Context understanding requires processing the text, and tokenizing the words by recognizing the word sense. Processing the text of the news articles requires time. And, most of the time, news search engines do not have enough time for processing the text. Thus, PageRank provides a sustainable timeline for the news sources for rankings.
PageRank is a quick signal for search engines to show the authenticity of the news web source. The highly cited sources are ranked higher, and longer on the top stories. Usually, Google protects the high PageRank sources by trusting the judgment of the websites. But, fact-finding algorithms do not use PageRank mostly, unless they couldn't decide by looking at other factors, or they do not have enough resources to process the text among the hundreds of sources.
News ranking algorithms differentiate opinions, reports, and breaking news from each other. News-related entities, their co-existence, and contextual relations change. Google inventors suggest differentiation of these entities from each other for a proper news categorization.
News categorization is important to match the interested topics of the users in queryless news feeds such as Google Discover. Google Discover is a queryless news feed that serves news stories according to the users' interest areas.
An opinion for news might be misleading. Some news titles might be too harsh, or strict. Search engines use these headlines to differentiate the non-trustworthy news sources from the trustworthy ones. And, opinions of journalists or their different interpretations of the events might change the rankings of a document according to the fact-finding algorithms.
SEO Case Study - Hangikredi.com From 12 March to 24 September Core UpdateKoray Tugberk GUBUR
Start Summary:
"131% Organic Session Increase in 5 Months
62% Impression Increase in 5 Months
144% Clicks Increase in 5 Months"
This SEO Case study is about Google Core Updates and their impacts on biggest financial institution website in Turkey.
I have started to work in Hangikredi.com at 26 March 2019. But, the company's website had been affected by 12 March Google Core Update very negatively.
I had started to work in here while a crisis had been happening.
I had examined the web site and figured it out that the real problems were crawl budget, authority signasl and relevancy-entity connection. I have activated social media, Google My Bussiness accounts, I have entered financial forums, every other alternative channel. I created a news publisher network about us. I cleaned the misleading status codes, HTML and CSS mistakes, optimised meta tags, fixed the redirection chains, I used the image compressions and deleted lots of unnecessary URL and their contents, I created the internal link structure from scratch.
Until 5 June Google Core Update, we were winners again.
We had regained all of our traffic lost. Until 1 August server atack, we were okay, then in one day, everything went wrong.
I had started from 0 again...
I had been optimising web site's offpage signals for regain the trust of Google AI and I had been supporting this strategy with onpage elements.
After 24th September Google Core Update, there was another success. We breaked the crawl load/rate record, avarage site position, CTR and impression, click records for site history.
In this CASE Study, you are gonna find details of a SEO Success Story with graphics and also some funny cencor images from my life.
End Summary:
"12 March, 5 june and 24 September Google Core Updates with 1 August Server Atack are the milestones of this SEO Casse Study. You will find all details from our view of point. I hope you will like it."
SEO Başarı Hikayesi - Hangikredi.com 12 Mart'tan 24 Eylül Google Core Güncell...Koray Tugberk GUBUR
Özeti Başlat:
"5 Ayda% 131 Organik Oturum Artışı
5 Ay İçinde% 62 Gösterim Artışı
5 Aylık% 144 Tıklama Artışı "
Bu SEO Vaka çalışması, Google Çekirdek Güncellemeleri ve Türkiye'deki en büyük finansal kurum web sitesine etkileri ile ilgili.
Hangikredi.com'da 26 Mart 2019'da çalışmaya başladım. Ancak şirketin web sitesi 12 Mart Google Çekirdek Güncellemesi'nden çok olumsuz etkilendi.
Bir kriz yaşanırken burada çalışmaya başladım.
Web sitesini inceledim ve asıl sorunların tarama bütçesi, otorite işareti ve alaka düzeyi-işletme ilişkisi olduğunu anladım. Sosyal medyayı, Google İş Hesaplarım'ı etkinleştirdim, diğer tüm alternatif kanallardan finansal forumlara girdim. Bizimle ilgili bir haber yayıncı ağı yarattım. Yanıltıcı durum kodlarını, HTML ve CSS hatalarını temizledim, meta etiketleri optimize ettim, yönlendirme zincirlerini düzelttim, görüntü sıkıştırma kullandım ve birçok gereksiz URL ve içeriğini sildim, iç bağlantı yapısını sıfırdan yarattım.
5 Haziran’dan Google Çekirdek Güncelleme’ye kadar tekrar kazandık.
Kaybettiğimiz bütün trafiğimizi geri kazandık. 1 Ağustos sunucu atack kadar, biz iyiydik, sonra bir gün, her şey ters gitti.
Yine 0'dan başladım ...
Web sitemizin offpage sinyallerini Google AI’ın güvenini yeniden kazanmak için optimize ediyordum ve bu stratejiyi onpage öğeleriyle destekliyordum.
24 Eylül Google Çekirdek Güncellemesi’nden sonra başka bir başarı daha oldu. Tarama yükü / oranı kaydını, ortalama site konumunu, TO'yu ve gösterimini, site geçmişi için tıklama kayıtlarını kırdık.
Bu CASE Çalışmasında grafikler içeren bir SEO Başarı Hikayesinin ayrıntılarını ve hayatımdaki bazı komik cencor resimlerini bulacaksınız.
Bitiş Özeti:
"12 Mart, 5 Haziran ve 24 Eylül 1 Ağustos Sunucu ile Google Çekirdek Güncellemeleri Atack, bu SEO Casse Çalışmasının kilometre taşlarıdır. Tüm detayları bizim açımızdan göreceksiniz. Umarım beğenirsiniz."
SGE, New Features in Google Search & How to Respond.pdfLily Ray
Lily Ray presented at the 2023 Engage PDX conference in Portland, Oregon about Google's Search Generative Experience (SGE), how it works, and concerns about SGE and its impact on SEO.
Different types of graphs and when you should use each + some random visuals I've always found useful.
Patrick Stox presenting at Digital Elite Day 2020
Semantic Search Engine: Semantic Search and Query Parsing with Phrases and En...Koray Tugberk GUBUR
Semantic Search Engines can understand human language to analyze the need behind a query. Instead of focusing, string, or word matching, a semantic search engine focuses on concepts, intents, and relations of named entities. Taxonomy, ontology, onomastics, semantic role labeling, relation detection, lexical semantics, entity extraction, recognition, resolution can be used by semantic search engines. In this PDF file, semantic search engines' evolution will be processed based on Google Search Engine's research papers, patents, and official announcements. From 1998 to 20021, search's and search engines' evolution, from strings to things, from phrases to entities will be told along with query processing, and parsing methodology changes.
As opposed to lexical search, semantic searching searches for meaning, not meaningless matches of the query words. Semantic search attempts to increase the relevancy of results by understanding searchers' intents and the context of terms in the searchable dataspace, whether online or within a closed system. The right semantic search content is a blend of natural language, focuses on the intent of the user, and considers other topics the user may be interested in.
Ontologies, XML, and other structured data sources can be used to retrieve knowledge using semantic search according to some authors. The use of such technologies provides a mechanism for creating formal expressions of domain knowledge that are highly expressive and may allow the user to express more detailed intent during query processing.
BrightonSEO March 2021 | Dan Taylor, Image Entity TagsDan Taylor
My talk from BrightonSEO 2021; focusing on using Google's image category labels (glancing into the Knowledge Graph and Google's image annotation processes) for better topic research and content optimization.
The Python Cheat Sheet for the Busy MarketerHamlet Batista
What percentage of an Inbound marketer's day doesn't involve working with spreadsheets? How much of this work is time-consuming and repetitive? In this interactive session, you will learn how to manipulate Google Sheets to automate common data analysis workflows using Python, a very easy to use programming language.
Understanding Semantic Search and AI Content to Drive Growth in 2023 March 2023TysonStockton1
Exploring modern search engines, semantic search, and AI technology to better understand how we can integrate into SEO strategy and content initiatives.
With the rise of ChatGPT there has been a lot of discussion around if SEO content is good or bad. To best determine how to leverage this technology in SEO workflows we must revisit how a modern search engine works and where we are at with AI technology.
Topics Covered:
1. Intro (Speaker, LLM, Will AI replace you)
2. AI for SEO
3. Understanding Prompts
4. How we @Botpresso Use AI (Python Scripts & Case Study)
5. DOs & DONTs
6. Tools
7. 10 Commandments
8. AI-driven Prompt Mastery 🎁
AI Prompts for SEO E-book: https://botpresso.com/ai-prompts-for-seo/
Crawling, indexation & the impact on performance | Brighton SEOMartin Sean Fennon
Brighton SEO presentation given by Martin Fennon, the Head of SEO for Ayima. This talk covers crawling, indexation & the tangible impact reviewing these elements can have on performance
Lexical Semantics, Semantic Similarity and Relevance for SEOKoray Tugberk GUBUR
Lexical semantics and relations between words include relations of superiority, inferiority, part, whole, opposition, and sameness between the meanings of words. The same word can be a meronymy, hyponym, or antonym of another word, depending on the word before or after it. The lexical relation value of the first word can affect the structure of the next word, affecting the context of the sentence and the Information Retrieval Score. Information Retrieval Score is the score that determines how much content is related to a query, how close the different variants of the related query are, and the structure processed by the search engine’s query processor to the relevant document. A higher information retrieval score represents better relevance and possible click satisfaction.
The problem with a semi-structured and distracting context for Information Retrieval Score is that, if a document is not configured for a single topic, the IR Score can be diluted by the two different contexts resulting in a relative rank lost to another textual document.
IR Score Dilution involves badly structured lexical relations, along with bad word proximity. The relevant words that complete each other within the meaning map should be used closely, within a paragraph or section of the document, to signal the context in a more clear way to increase the IR Score. A search engine can check whether the document contains the hyponym of the words within the query or not. A possible query prediction can be generated from the hypernyms of the query. A search engine can check only the anchor texts to see whether there is a word within the “hyponym distance” which represents the hyponym depth between two different words.
Lexical Relations can represent the semantic annotations for a document. A semantic annotation is a word that describes the document overall in terms of category and main context that carries the purpose of the document. A semantic annotation can contain the main entity of the document or a general concept for covering a broader meaning area (knowledge domain). Semantic Annotations can be generated with the lexical relations between words. A semantic annotation can be used to match the document to the query. Semantic annotations are factors for a better IR Score.
A search engine can generate phrase patterns from the lexical relationships between words within the queries or the documents. A phrase pattern contains sections that define a concept with qualifiers. Phrase patterns can contain a hyponym just after an adjective, or a hypernym with the antonym of the same adjective. Most of these connections and patterns are used within the Recurrent Neural Network (RNN) for the next word prediction. A phrase pattern helps a search engine to increase its confidence score for relating the document to the specific query, or the meaning of the query.
Coronavirus and Future of SEO: Digital Marketing and Remote CultureKoray Tugberk GUBUR
I have attended a great SEO and Digital Marketing webinar with Founder of Stradiji and SEMRush Turkey Lead Mr. Mert Erkal and My Dearest Friend and SEO Consultant Atakan Erdoğan.
Small Note: After I uploaded the presentation, Google launched a new Covid-19 news address like Bing/covid-19. You may want to look at it -> https://www.google.com/covid-19
I have prepared a Presentation about Coronavirus's Effects on Search Engine Optimization (SEO).
You will find Coronavirus's changing effects on Digital Marketing and psychology of global society while using Search Engines.
I also have focused on Search Engine's and Social Media Brands, E-commerce Site's reflexes against Coronavirus Pandemic.
You will see the web sites and categories who earn more traffic and lose traffic. You will also see conversion rate differences because of Coronavirus.
Also, I have told about Search Engine's differences and their attitude against the Coronavirus Pandemic, their future, their updates during the pandemic.
In the last part, you will see some new 2020 Web Technology and Design Trends with AI.
There are also Google Researches for better Search Engine technologies.
Questions:
1- What are the differences between Yandex, Google, Bing, and Duckduckgo for Coronavirus Pandemic?
2- Twitter, Instagram, Amazon or Apple, what are they doing?
3- What do people search most for during the Coronavirus Crisis?
4- What changes from country to country?
5- What are the future technologies of Web and App?
6- How and why do Search Engines improve AI, what is the last events?
7- Which sites loose traffic and which earn more?
8- Lots of quotes from International SEOs about the pandemic.
And more...
I am Koray Tuğberk GÜBÜR and a Holistic SEO Expert.
I sincerely thank you for my Dearest Friend Atakan Erdoğan and Mr. Mert Erkal for this awesome webinar opportunity and experience.
To watch the webinar, please visit Stradiji's Official Youtube Channel.
https://www.youtube.com/watch?v=V4sJTNcRqaM&t=100s
Opinion-based Article Ranking for Information Retrieval Systems: Factoids and...Koray Tugberk GUBUR
How Search Engines Leverage Opinion-based Articles for Ranking?
Search engines use opinions, and factoids to understand the consensus. News search engines use different reports, and opinions in their search results to satisfy the urgent news information needed by the newsreaders. The news search engines differentiate disinformation from information to protect the newsreaders. Google, Microsoft Bing, Yandex, and DuckDuckGo have different algorithms and prioritization for classifications of the news sources, or prioritization of the news, and newsworthy topics.
Corroboration of the Web Answers from the Open Web is a research paper from Amelia Marian and Minji Wu explaining how a search engine can rank information according to its accuracy.
Google started to explain that the Expertise-Authoriteveness-Trustworthiness is the most important group of signals to be sure that a result won't shame the search engine. Embarrassment factors for the search engines involve wrong information on a news title on the news story, or a wrong featured snippet. A search engine might be shame due to the bad result that is ranking on the SERP.
Dense-retrieval, context scoring, named entity recognition, semantic role labeling, truth ranges, fix points, confidence score, query processing, and parsing.
Context understanding requires processing the text, and tokenizing the words by recognizing the word sense. Processing the text of the news articles requires time. And, most of the time, news search engines do not have enough time for processing the text. Thus, PageRank provides a sustainable timeline for the news sources for rankings.
PageRank is a quick signal for search engines to show the authenticity of the news web source. The highly cited sources are ranked higher, and longer on the top stories. Usually, Google protects the high PageRank sources by trusting the judgment of the websites. But, fact-finding algorithms do not use PageRank mostly, unless they couldn't decide by looking at other factors, or they do not have enough resources to process the text among the hundreds of sources.
News ranking algorithms differentiate opinions, reports, and breaking news from each other. News-related entities, their co-existence, and contextual relations change. Google inventors suggest differentiation of these entities from each other for a proper news categorization.
News categorization is important to match the interested topics of the users in queryless news feeds such as Google Discover. Google Discover is a queryless news feed that serves news stories according to the users' interest areas.
An opinion for news might be misleading. Some news titles might be too harsh, or strict. Search engines use these headlines to differentiate the non-trustworthy news sources from the trustworthy ones. And, opinions of journalists or their different interpretations of the events might change the rankings of a document according to the fact-finding algorithms.
SEO Case Study - Hangikredi.com From 12 March to 24 September Core UpdateKoray Tugberk GUBUR
Start Summary:
"131% Organic Session Increase in 5 Months
62% Impression Increase in 5 Months
144% Clicks Increase in 5 Months"
This SEO Case study is about Google Core Updates and their impacts on biggest financial institution website in Turkey.
I have started to work in Hangikredi.com at 26 March 2019. But, the company's website had been affected by 12 March Google Core Update very negatively.
I had started to work in here while a crisis had been happening.
I had examined the web site and figured it out that the real problems were crawl budget, authority signasl and relevancy-entity connection. I have activated social media, Google My Bussiness accounts, I have entered financial forums, every other alternative channel. I created a news publisher network about us. I cleaned the misleading status codes, HTML and CSS mistakes, optimised meta tags, fixed the redirection chains, I used the image compressions and deleted lots of unnecessary URL and their contents, I created the internal link structure from scratch.
Until 5 June Google Core Update, we were winners again.
We had regained all of our traffic lost. Until 1 August server atack, we were okay, then in one day, everything went wrong.
I had started from 0 again...
I had been optimising web site's offpage signals for regain the trust of Google AI and I had been supporting this strategy with onpage elements.
After 24th September Google Core Update, there was another success. We breaked the crawl load/rate record, avarage site position, CTR and impression, click records for site history.
In this CASE Study, you are gonna find details of a SEO Success Story with graphics and also some funny cencor images from my life.
End Summary:
"12 March, 5 june and 24 September Google Core Updates with 1 August Server Atack are the milestones of this SEO Casse Study. You will find all details from our view of point. I hope you will like it."
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.
This lectures provides students with an introduction to natural language processing, with a specific focus on the basics of two applications: vector semantics and text classification.
(Lecture at the QUARTZ PhD Winter School (http://www.quartz-itn.eu/training/winter-school/ in Padua, Italy on February 12, 2018)
English dictionaries since 1755 have attempted to present succinct statements of the meaning(s) of each word. A word may have more than one meaning but, so the theory goes, each meaning can in principle be summarized in a neat paraphrase that is substitutable (in context) for the target word (the definiendum). Such paraphrases must be so worded that the the substitution can be made without changing the truth of what is said – salva veritate, in Leibniz’s famous phrase. Building on Leibniz, philosophers of language such as Anna Wierzbicka have argued that the duty of the lexicographer is to “seek the invariant”.
In this presentation, I argue that this view of word meaning and definition may be all very well as a principle for developing stipulative definitions of terminology in scientific discourse, but it has led to serious misunderstandings about the nature of meaning in natural language, creating insuperable obstacles for the understanding of how word meaning works. As a result, linguists from Bloomfield to Chomsky and philosophers of language from Leibniz to Russell – great thinkers all – have been unable to say anything true or useful about meaning in language.
I argue that, instead, lexicographers should aim to discover patterns of word use in large corpora, and associate meanings with patterns instead of (or as well as) words in isolation.
They should also distinguish normal uses of each word from exploitations of norms.
From Natural Language Processing to Artificial IntelligenceJonathan Mugan
Overview of natural language processing (NLP) from both symbolic and deep learning perspectives. Covers tf-idf, sentiment analysis, LDA, WordNet, FrameNet, word2vec, and recurrent neural networks (RNNs).
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
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?
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 is many things, including the name of a Google Search algorithm update. There is lots of confusion as to what Google BERT is, where it has come from and what SEOs and marketers need to do about it (if anything). Here we look at the solutions the introduction of Google BERT by Google seeks to provide and explore the background to natural language processing and computational linguistics.
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.
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
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.
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.
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.
Digital marketing is the art and science of promoting products or services using digital channels to reach and engage with potential customers. It encompasses a wide range of online tactics and strategies aimed at increasing brand visibility, driving website traffic, generating leads, and ultimately, converting those leads into customers.
https://nidmindia.com/
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.
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.
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/
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.
Most small businesses struggle to see marketing results. In this session, we will eliminate any confusion about what to do next, solving your marketing problems so your business can thrive. You’ll learn how to create a foundational marketing OS (operating system) based on neuroscience and backed by real-world results. You’ll be taught how to develop deep customer connections, and how to have your CRM dynamically segment and sell at any stage in the customer’s journey. By the end of the session, you’ll remove confusion and chaos and replace it with clarity and confidence for long-term marketing success.
Key Takeaways:
• Uncover the power of a foundational marketing system that dynamically communicates with prospects and customers on autopilot.
• Harness neuroscience and Tribal Alignment to transform your communication strategies, turning potential clients into fans and those fans into loyal customers.
• Discover the art of automated segmentation, pinpointing your most lucrative customers and identifying the optimal moments for successful conversions.
• Streamline your business with a content production plan that eliminates guesswork, wasted time, and money.
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.
When most people in the industry talk about online or digital reputation management, what they're really saying is Google search and PPC. And it's usually reactive, left dealing with the aftermath of negative information published somewhere online. That's outdated. It leaves executives, organizations and other high-profile individuals at a high risk of a digital reputation attack that spans channels and tactics. But the tools needed to safeguard against an attack are more cybersecurity-oriented than most marketing and communications professionals can manage. Business leaders Leaders grasp the importance; 83% of executives place reputation in their top five areas of risk, yet only 23% are confident in their ability to address it. To succeed in 2024 and beyond, you need to turn online reputation on its axis and think like an attacker.\
Key Takeaways:
- New framework for examining and safeguarding an online reputation
- Tools and techniques to keep you a step ahead
- Practical examples that demonstrate when to act, how to act and how to recover
Short video marketing has sweeped the nation and is the fastest way to build an online brand on social media in 2024. In this session you will learn:- What is short video marketing- Which platforms work best for your business- Content strategies that are on brand for your business- How to sell organically without paying for ads.
Mastering Multi-Touchpoint Content Strategy: Navigate Fragmented User JourneysSearch Engine Journal
Digital platforms are constantly multiplying, and with that, user engagement is becoming more intricate and fragmented.
So how do you effectively navigate distributing and tailoring your content across these various touchpoints?
Watch this webinar as we dive into the evolving landscape of content strategy tailored for today's fragmented user journeys. Understanding how to deliver your content to your users is more crucial than ever, and we’ll provide actionable tips for navigating these intricate challenges.
You’ll learn:
- How today’s users engage with content across various channels and devices.
- The latest methodologies for identifying and addressing content gaps to keep your content strategy proactive and relevant.
- What digital shelf space is and how your content strategy needs to pivot.
With Wayne Cichanski, we’ll explore innovative strategies to map out and meet the diverse needs of your audience, ensuring every piece of content resonates and connects, regardless of where or how it is consumed.
10 Video Ideas Any Business Can Make RIGHT NOW!
You'll never draw a blank again on what kind of video to make for your business. Go beyond the basic categories and truly reimagine a brand new advanced way to brainstorm video content creation. During this masterclass you'll be challenged to think creatively and outside of the box and view your videos through lenses you may have never thought of previously. It's guaranteed that you'll leave with more than 10 video ideas, but I like to under-promise and over-deliver. Don't miss this session.
Key Takeaways:
How to use the Video Matrix
How to use additional "Lenses"
Where to source original video ideas
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.
18. But I will be talking about some concepts
covering:
Data Science
01
Information
Retrieval
02
Algorithms
03
Linguistics
04
Information
Architecture
05
Library
Science
Category
theory
19. Since… These are all areas
connected to how search
engines (try to) find the
right information, for the
right informational need at
the right time for the right
user
20. ‘information retrieval’ in web search
To extract informational resources to meet a
search engine user’s information need at time
of query.
21. Let us first take a very
simplistic look at how we
know search engines work
22. It’s just like gathering & organizing
books in a library system or using an
old card index system
23. But instead we are taking
words (or phrases) and
recording where they live
34. Relevance Matching to Query Requires:
Understanding meaning of words in content & query (What?)
Understanding meaning of word's context in content & query (What?)
Understanding of user’s context (Who / Where / When / Why?)
Understanding of collaboration (Past queries / popularity /
reinforcement / learning to rank)
43. Many websites
(and
webpages) are
not logically
organized at all
Unstructured data is voluminous
Filled with irrelevance
Lacks focus
Riddled with nuance
Lots of meaningless text and further
ambiguating jabber
44. Most text-filled web pages
could be considered
unstructured, noisy data
Blog == Blah Blah
45. Structured versus unstructured data
• Structured data – high
degree of organization
• Readily searchable by
simple search engine
algorithms or known search
operators (e.g. SQL)
• Logically organized
• Often stored in a relational
database
46. When we compare them with highly organized relational database systems
47. A form of structured (& semi-structured) data – Entities, Knowledge
Graphs, Knowledge Bases & Knowledge Repositories
48. “Entities help to bridge the
gap between structured
and unstructured data”
(Krisztian Balog, ECIR2019
Keynote)
56. Since website
is NOT ALL
unstructured
data even
before
structured
data markup
It can have a hierarchy
It can have weighted sections
It can have metadata
It (often) has a tree like structure
57. As long as there is
understanding of
notions of
categorical
‘inheritance’
60. Semi-
structured
data
• Hierarchical nature of a
website
• Tree structure
• Well sectioned and
including clear containers
and meta headings
• An ontology map between
semi and structured
77. When they can’t even tell the difference between Pomeranians and pancakes
78. They need
‘Text
cohesion’
Cohesion is the grammatical and
lexical linking within a text
or sentence that holds a text
together and gives it meaning.
Without surrounding words the
word bucket could mean
anything in a sentence
98. Coast and
Shore
Example
Coast and shore have a similar
meaning
They co-occur in first and second
level relatedness documents in a
collection
They would receive a high score in
similarity
99. Language models are trained on
very large text corpora or
collections (loads of words) to
learn distributional similarity
103. Continuous Bag of Words (CBoW)
(Method) or Skip-gram (Opposite of
CBoW)
Continuous Bag of Words -
Taking a continuous bag of
words with no context utilize a
context window of n size n-gram)
to ascertain words which are
similar or related using Euclidean
distances to create vector
models and word embeddings
113. Most language modellers are uni-directional
Source Text
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
They can traverse over the word’s context window from only left to right or
right to left. Only in one direction, but not both at the same time
114. They can only look at words in the context
window before and not the words in the rest of
the sentence. Nor sentence to follow next
120. BERT is different. BERT uses bi-directional
language modelling. The FIRST to do this
Source Text
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
Writing a list of random sentences is harder than I Initially thought it would be
Bert can see both the left and the right hand side of the target word
144. There are also
several types of
queries too
(Krisztian Balog,
ECIR, 2019)
Keyword queries (Normal keyword queries)
Keyword++ queries (Faceted / filtered
queries)
Zero-Query queries (User is the query)
Natural language queries
Structured queries (e.g. SQL)
168. What did you really mean when you searched for ‘Easter’?
When did
you search
for ‘Easter’?
A few weeks
before Easter
A few days
before Easter
During Easter
What you
mostly meant
When is
Easter?
Things to do
at Easter
What is the
meaning of
Easter?
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Editor's Notes
Anyway… back to words. Words are everywhere.
Is there any point in returning results from nearby if the speed at which the user is travelling will render the result useless in just a minute or two?
Better to utilize tools such as the accelerometer and understand the direction and speed that the user is going in to return the most appropriate results as suggestions
Their ambiguous and polysemic nature mean that search engines have to try to disambiguate their meaning in order to understand what the searcher meant and also to understand what the content me