Search Query Processing: The Secret Life of Queries, Parsing, Rewriting & SEO

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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.

Marketing

The Secret Life of Queries:
Parsing, Rewriting & SEO
Rebecca Berbel | Oncrawl
Koray Tuǧberk Gübür | Holistic SEO
slideshare.net/Oncrawl
@RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
^(([^:/?#]+):)?(//([^
/?#]*))?([^?#]*)(?([
^#]*))?(#(.*))?
https://www.google.com
/search?q=search+engine+k
eywords#anchor

#brightonSEO @RebBerbel @KorayGubur
WHAT
THAT
MEANT
FOR SEO
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
NOT
ANY
MORE.
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
LET'S
TAKE A
LOOK.
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
PARSING
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
Parsing a query

#brightonSEO @RebBerbel @KorayGubur
REWRITING
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
Query segments

#brightonSEO @RebBerbel @KorayGubur
Keyword clustering

#brightonSEO @RebBerbel @KorayGubur
Keywords → Questions

#brightonSEO @RebBerbel @KorayGubur
Question Templates

#brightonSEO @RebBerbel @KorayGubur
Query refinements

#brightonSEO @RebBerbel @KorayGubur
CONTEXT
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
User Intent

#brightonSEO @RebBerbel @KorayGubur
Location/Time

#brightonSEO @RebBerbel @KorayGubur
FINDING
ANSWERS
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
BERT

#brightonSEO @RebBerbel @KorayGubur
Candidate Passages

#brightonSEO @RebBerbel @KorayGubur
PHEW.
LET'S
TAKE A
STEP BACK.

#brightonSEO @RebBerbel @KorayGubur
THERE'S MORE
(but we'll stop here)

#brightonSEO @RebBerbel @KorayGubur
GOOGLE DOES NOT USE
THE TEXT YOU TYPED
TO SEARCH FOR
RESULTS.
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
WHAT
THAT
MEANS
FOR SEO
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
BUILD
TOPICAL
RELEVANCE
Oncrawl / Koray

#brightonSEO @RebBerbel @KorayGubur
REMEMBER
NEURAL
MATCHING
Danny Sullivan (Twitter)

#brightonSEO @RebBerbel @KorayGubur
GROUP
TARGETED
QUERIES
Stefan Neefischer

#brightonSEO @RebBerbel @KorayGubur
THINK
SEARCH
INTENT
Johanna Maier / Lidia Infante / Lazarina Stoy

#brightonSEO @RebBerbel @KorayGubur
DOES IT
WORK?
#brightonSEO @RebBerbel @KorayGubur

#brightonSEO @RebBerbel @KorayGubur
Semantic networks & topical relevance

#brightonSEO @RebBerbel @KorayGubur
Semantic networks & topical relevance
10K to 70K
clicks per month
(5 months)
10K to 200K+
clicks per month
(5 months)
0 to 330K+
clicks per month
(6 months)
+400%
growth
(6 months)

#brightonSEO @RebBerbel @KorayGubur
Thank you!
@RebBerbel
rebecca@oncrawl.com
@KorayGubur
Holistic SEO
ktgubur@holisticseo.digital
#brightonSEO @RebBerbel @KorayGubur

40 Deep #SEO Insights for 2023: -In 2022, I told to focus on Natural Language Generation, and it happened. -In 2023, F-O-C-U-S on "Information Density, Richness, and Unique Added Value" with Microsemantics. I call the collection of these, "Information Responsiveness". 1/40 🧵. 1. PageRank Increases its Prominence for Weighting Sources Reason: #AI and automation will bloat the web, and the real authority signals will come from PageRank, and Exogenous Factors. The expert-like AI content and real expertise are differentiated with historical consistency. 2. Indexing and relevance thresholds will increase. Reason: A bloated web creates the need for unique value to be added to the web with real-world expertise and organizational signals. The knowledge domain terms, or #PageRank, will be important in the future of a web source. 3. AI and #automation filters will be created. Reason: Google needs to filter the websites that publish 500 articles a day on multiple topics to find non-expert websites. This is already happening. 4. #Google will start to make mistakes in filtering websites that use spam and AI. Reason: The need for AI-generated content filtration forced Google to check and audit "momentum", in other words, content publication frequency. I used the "momentum" first in TA Case Study. 5. Google uses #Author Vectors, and Author Recognition. Reason: LLMs use certain types of language styles and word sequences by leaving a watermark behind them. It is easy to understand which websites do not use a real expert for their articles, and content to differentiate. 6. #Microsemantics will be the name of the next game. Reason: The bloating on the web will create bigger web document clusters, and being a representative source will be more important. Thus, micro-differences inside the content will create higher unique value. 7. Custom #LLMs will be rented. Reason: Custom and unique LLMs will be trained and rented to the people who try to create 100 websites with 100,000 content items per website. NLP in SEO will show its true monetary value in mid-2023. 8. Advanced Semantic SEO will be a must for every SEO. Reason: 20 years of websites will lose their rankings to the new websites that come with 60,000 articles. This creates the need for advanced #Semantics and Lingusitics capabilities for SEOs. 9. Cost-of-retrieval will be a base concept for #SEO, as TA. Reason: TA explains a big portion of how the web works. Information Responsiveness and Cost-of-retrieval will complete it further. For two books, I will be publishing only these two concepts. 10. Google Keys Reason: The biggest Google leak after Quality Rater Guidelines will happen in 2023. And, I will be involved, but no more information, for now, I am not allowed to share more. Check the slides for the next SEO Insights for 2023. #searchengineoptimization #future #nlp #semantic #chatgpt #ai #content #quality #publishing #trend #seotrend #seo #searchengineoptimisation

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Semantic Content Networks are the semantic networks of things with relations, directed graphs, attributes and facts. Every declaration, and proposition for semantic search represent a factual repository. Open Information Extraction is a methodology for creation of a semantic network. The Knowledge Base and Knowledge Graph are connected things to each other in terms of factual repository usage. The Knowledge Base represents a factual repository with descriptions and triples. Knowledge Graph is the visualized version of the Knowledge Base. A semantic network is knowledge representation. Semantic Network is prominent to understand the value of an individual node, or the similar and distant members of the same semantic network. Semantic networks are implemented for the search engine result pages. Semantic networks are to create a factual and connected question and answer networks. A semantic network can be represented and consist of from textual and visual content. Semantic Network include lexical parts and lexical units. Links, Nodes, and Labels are parts of the semantic networks. Procedural Parts are constructors, destructors, writers and readers. Procedural parts are to expand the semantic networks and refresh the information on it. Structural Part has links and nodes. Semantic part has the associated meanings which are represented as the labels. The semantic content networks have different types of relations and relation types. Semantic content networks have "and/OR" trees. Semantic Content Networks have "Relation Type Examples" with "is/A" hierarchies. Semantic Content Networks have "is/Part" Hierarchy. Inheritance, reification, multiple inheritance, range queries and values, intersection search, complex semantic networks, inferential distance, partial ordering, semantic distance, and semantic relevance are concepts from semantic networks. Semantic networks help understanding semantic search engines and the semantic SEO. Because, it contains all of the related lexical relations, semantic role labels, entity-attribute pairs, or triples like entity, predicate and object. Search engines prefer to use semantic networks to understand the factuality of a website. Knowledge-based Trust is related to the semantic networks because it provides a factuality related trust score to balance the PageRank. The knowledge-based Trust is announced by Luna DONG. Ramanathan V. Guha is another inventor from the Google and Schema.org. He focuses on the semantic web and semantic search engine behaviors. He explored and invented the semantic search engine related facts. Semantic Content Networks are used as a concept by Koray Tuğberk GÜBÜR who is founder of Holistic SEO & Digital. Expressing semantic content networks helps to shape the semantic networks via textual and visual content pieces. The semantic content networks are helpful to shape the truth on the open web, and help a search engine to rank a website even if there is no external PageRank flow.

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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.

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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.

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This article delves into the concepts of Semantic SEO, Topical Authority, and PageRank, exploring their relationships and how they benefit both website owners and search engines. By leveraging Natural Language Processing (NLP) techniques, Semantic SEO improves search engine comprehension of content and enhances user experience, ultimately leading to better search results. In the ever-evolving world of Search Engine Optimization (SEO), understanding the intricate connections between Semantic SEO, Topical Authority, and PageRank is crucial for webmasters, content creators, and marketers. These concepts play a vital role in enhancing the visibility and relevance of websites in search results. Semantic SEO: Going Beyond Keywords Semantic SEO involves optimizing content by focusing on the meaning and context of words, phrases, and sentences rather than merely targeting specific keywords. This is achieved through NLP techniques such as topic modeling, sentiment analysis, and entity recognition, which allow search engines to comprehend the true essence of content. Topical Authority: Establishing Expertise and Trustworthiness Topical Authority refers to the perceived expertise of a website or content creator in a specific subject area. By producing high-quality, relevant, and in-depth content, websites can establish themselves as authorities, earning the trust of both users and search engines. This translates into higher search rankings and increased visibility. PageRank: Measuring the Importance of Webpages PageRank is an algorithm used by Google to determine the significance of a webpage by analyzing the quality and quantity of its inbound links. A higher PageRank implies that a website is more authoritative and valuable, thus warranting a better position in search results. The Interrelation of Semantic SEO, Topical Authority, and PageRank Semantic SEO, Topical Authority, and PageRank are interconnected concepts that work in tandem to improve a website's search performance. By focusing on Semantic SEO, content creators can enhance their Topical Authority and establish a solid online presence. This, in turn, can lead to higher PageRank and improved search visibility. The Benefits of Semantic SEO for Search Engines Semantic SEO not only benefits website owners but also search engines by reducing the cost of understanding documents. With the help of NLP techniques, search engines can efficiently analyze and comprehend content, making it easier to identify and index relevant webpages. This ultimately leads to more accurate search results and a better user experience. In conclusion, embracing Semantic SEO, Topical Authority, and PageRank is essential for achieving higher search rankings and increased online visibility. By leveraging NLP techniques, Semantic SEO offers a more sophisticated and efficient approach to understanding and optimizing content, ultimately benefiting both website owners and search engines.

Coronavirus and Future of SEO: Digital Marketing and Remote Culture

Koray 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

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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."

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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.

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Simple guidelines for your online presence and marketing, utilizing basics of digital marketing, as well as the main ideas behind antifragility and asymmetry . The main online marketing strategy discussed is establishing yourself (company) as an authority/expert in your field. You do this very well and consistently such that people want to work with you (customers, investors, collaborators, etc.). The main tool for establishing your presence is creating useful content that demonstrates your expertise. The main focus is on timeless topics to have time work with you, not against you. Good luck!

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