Everything started with my thoughts on a article written by Damian Thompson and called
What The Heck Is Semantic SEO & Should You Care At All?
At the end of the day it doesn’t matter whether you call it Semantic SEO or just SEO. Adapting to the semantic search topography will be part of every SEO’s job description going forward. Like it or not.
But, a caveat: semantic web is NOT the same as Semantic SEO –http://goo.gl/B1N9Ww
Top tools to help you with your semantic SEO efforts:
Übersuggest – www.ubersuggest.org
CISE – Conceptual Intelligence Search Engine CISE – http://goo.gl/BdaUo8 – by Peter Hatherley
PS Did a bit of googling and found a good definition of the term ‘Semantic SEO” by Mashable and Erin Everhart:
“Semantic search uses artificial intelligence in order to understand the searcher’s intent and the meaning of the query rather than parsing through keywords like a dictionary. When you search now, Google gives you results based solely on the text and the keywords that you put in that search. Essentially, Google gives you its best guess.” – http://goo.gl/MB8Mnv
In simple words Semantic SEO is dealing with search results that do not necessarily contain the keywords in your copy. But trust me, it’s not just a guessing game.
Then a conversation started.
Aaron Bradley: Omi Sido, PS Did a bit of googling and found a good definition of the term ‘Semantic SEO”…
Actually what you provided was a definition of semantic search – a pretty good one, but one that doesn’t actually address semantic SEO which would (a la the “O” in “SEO”) give a nod to optimizing for semantic search.
So what is it?
I’ll have a go (culled from http://bit.ly/1aLpw09), and invite others to weigh in!
Semantic SEO is optimizing for the entities and entity relationships that search engines identify in queries and return in results.
Omi Sido: Aaron Bradley, you are absolutely right and your definition (denotation) is spot on. I can’t even believe you wrote this article in 2013 when not many people were talking about semantic search and #seo .
On the other side I still find the definition given by Erin Everhart (I was so sure somebody will challenge me on this one (lol) as neither the article, nor this exact quote are actually talking about Semantic SEO) a good base for explaining what Semantic SEO is, especially to people just getting into the semantic world.
And last but not least this is one of the articles Google and Bing (mobile and desktop) are showing on page one 🙂 when asking the question: ‘what is semantic seo’ – https://goo.gl/WGVxFi, https://goo.gl/MGFmNq.
Bad google. Still a lot of room for improvements 🙂
Aaron Bradley: Thanks a lot Omi Sido – and I agree that Erin’s thumbnail description is an excellent one.
For what it’s worth, my go-to definition of semantic search (which I quote at the end of http://bit.ly/semsemtechbiz2013) is from Tamas Doszkocs:
“Semantic search is a search or a question or an action that produces meaningful results, even when the retrieved items contain none of the query terms, or the search involves no query text at all.”
Teodora Petkova: Omi Sido thanks for igniting this discussion. Aaron Bradley thanks for the definition (again these relationships… :-))
Raja Rethinam: Omi Sido, this is a wonderful introduction to semantic SEO. Never thought about it, but now I’m gonna pay more attention!
Love the picture 🙂
Aaron Bradley your definition is an excellent one.
Omi Sido: PS I’ve just noticed that many people are using the same definition when trying to explain Semantic SEO (hmm I thought I was unique 🙂 lol )
One probability would be: Google is displaying this article on page one for this query.
Is Google trying to tell us something (bemuse us) or are we confusing the search engine (David Amerland, Aaron Bradley)?
Is it possible that in the future we may have wrong answers given by Google just because people like one thing more over another 🙂
David Amerland: Omi Sido, I have started defining some terms (still a work in progress): http://goo.gl/zb8Wl6 and the Veracity question of search is key to the trustworthiness of the results and the inherent difficulty in manipulating them. Within semantic search there is a weighing algorithm that ascribes veracity values through citations (as opposed to mentions) and authority. So, to break this down a bit, if a lot of us say the same thing (i.e. because it is popular) and only some of us say the right thing (and we have authority) Google will display the authoritative version as opposed to the popular one.
This has the same fluid caveats as any real life equivalent. So if a lot of us say the same thing and keep on saying the same thing then whatever we are saying will start to splinter from the authoritative source’s definition and will start to become a thing which will have the potential to provide an alternative, acceptable definition by widespread acceptance. In many ways we experience that in RL with the fluidity of language and definitions as well as some grammatical forms where the incorrect version is used “coz it’s used” as opposed to the correct form (the word “data” springs to mind as the perfect example here – it’s plural but many engineers use it as if it’s singular instead of writing “datum”).
Aaron Bradley: David Amerland, what a great summary of how, in semantic search, authority can trump (or at least inform) popularity – thanks! (Literally bookmarked under “Authority”. Oh, did somebody say “Authoritah?” http://bit.ly/respect-my-authoritah)
The subject too brings to mind the Knowledge-Based Trust (KBT) method proposed by Google researchers (http://bit.ly/1zRQtdG), which would have Google rank a resource based on “the correctness of factual information provided by the source.”
KBT is a fascinating rabbit hole I urge you to dart down Omi Sido, but I won’t journey there myself now except to note the importance in KBT of the model that “jointly estimates the correctness of extractions and source data, and the trustworthiness of sources.” That is, judging what’s the “best” answer to a query involves make an assessment of the quality of the dataalong with the trustworthiness and veracity of the data provider (of which David speaks).
It strikes me more and more as discussions like those stimulated by KBT arise that the challenges faced by the search engines now are increasingly – and increasingly baldly – epistemological. Hell, even phenomenological. A bigger and bigger part of search engine research is being directed at figuring out how machines can answer philosophical questions that we humans not only grapple with, but often do so with great difficulty.
How do we tell a fact from a non-fact? How do we distinguish a pretty good fact from a really good fact? What are we to make of two seemingly authoritative but contradictory facts?
Those are now the sort of questions that machines are endeavoring to answer. Or required to answer in the narrow sense that a search engine needs at the very least to always provide a preferential answer. A search engine responding to a query, unlike a human talking to another human, can’t say, “well, we disagree on that, but since it’s not important you hold on to your views, I’ll hold on to mine, and we’ll go have a beer together.” A search engine can’t waffle it’s way out of producing a result.
And these discussions are arising more often with our increased reliance on machines (and especially mobile devices) to provide us with answers, and however trivial it may seem for most queries, there’s always going to be an answer that’s selected from alternatives on your behalf. Fairly innocuous in consequence if your question is “where is the nearest Starbucks?” but perhaps less so for “best local physical therapy.”
Oh, and thanks Raja Rethinam and Teodora Petkova!
David Amerland: Aaron Bradley yep, love what you added here. This is where all the cognitive computing magic is taking us. OK for closed data sets as Watson demonstrated with medical research but a bit of problem in the open web. I have a suspicion that context, in this sense, creates a closed data set of sorts that would define a ‘best’ answer but that would mean that at some point my context might trump yours and I get a better answer than you, maybe? It would be great to see our devices deal with that. 😉
Teodora Petkova: On behalf of John Kellden (without him knowing that:)) I am upgrading this thread to epic [marginalia: “the challenges faced by the search engines now are increasingly – and increasingly baldly – epistemological. Hell, even phenomenological. A bigger and bigger part of search engine research is being directed at figuring out how machines can answer philosophical questions that we humans not only grapple with, but often do so with great difficulty.” cit. Aaron Bradley]
John Kellden: Epic, Teodora Petkova is epic.
I believe we’re only in the beginning of the Avatar Metalogues – where we little by little rediscover that our digital selves are already engaged in metalogues.
With our ten bits per second processing speed, we can’t grok these processes – with one of the results a cornucopia of articles, bringing parts of this down to a level where we can at least begin to understand some of it.
However, if we switch to pattern recognition mode, we can already begin to see a convergence, between Intelligence Augmentation, Semantic Search, Semiotic Entities, Artificial Intelligence, Network-centric heuristics, and tons of other related fields.
Granted, that our human analog pattern recognition is somewhat buggy, belief-biased (shortcuts in) inference ladders, cognitive fallacies and much more – and here is where the algorithms brings a much welcome bonus gift – a slightly more objective additional feedback loop.
Aaron Bradley: Ha, thanks Teodora Petkova The “ha” because I’ve been writing a book about the phenomenological and epistemological implications of globally-used search engines for years.
Unfortunately (or perhaps fortunately for the reading public) I’ve mostly been writing it in my head, so Theory of the Search will almost certainly never see the light of day.
(Those of you of a post-structuralist bent may recognize that as a nod to Roland Barthes’ “Théorie du texte” (Encyclopædia Universalis, 1974), to which many of my ideas in this realm are indeed indebted, and is a piece which everyone should read.)
David Amerland: Aaron Bradley how can we get this book out of your head? Do we really need to hold you down and operate? 😀
Aaron Bradley: David Amerland You’d be disappointed. The dejected look on the face of that zombie that had been moaning “braaaaains” when he opened my skull cap was simply heartbreaking.
David Amerland: Aaron Bradley you’re cracking me up on a busy Friday 🙂
John Kellden: According to latest Semantic Search theory, the cracks in our heads is where the entity can peer out into the world. 🙂
David Amerland: John Kellden LOL, in that case Aaron Bradley has got a headstart on us thanks to his zombie encounter.
Teodora Petkova: John Kellden, feels like our “human analog pattern recognition” is biased by our bodies too, plus our lost connection to the group. Funny that you said cracks 🙂 Yesterday I while I was walking in a park I was thinking about David Amerland‘s comment: “I have a suspicion that context, in this sense, creates a closed data set of sorts that would define a ‘best’ answer but that would mean that at some point my context might trump yours ” The train of thought went this way: by default context is circum-sribing text, in a way it encircles it. The only way we can link texts from one circle (i.e. context) to another is through cracks in the context. Thankfully we have these cracks in the form of ambiguity, of biases or other “human” stuff. On the open web, we can have them as bridges between ontologies.
Teodora Petkova: Aaron Bradley, this is such a wonderful thing. Thanks for deciding to write that book soon. :)) [excuse my attempt for a tiny rhetorical approach :D] That would be a magnificent read, plus I will feel less weird (officially) when I tell people that web and text have so many functional and formal similarities.
Aaron Bradley: Teodora Petkova, The web is a text, or at least a vast corpus from which narratives are endlessly constructed, like the journey that weaves in and out of queries and websites, queries and websites.
Which means you can approach it with the same textual analysis tools that the likes of Foucault and Barthes and Derrida wielded to produce so many devastating insights into language.
The post-structuralist notion that there is no way a text can be said to have a canonical meaning – that a text is in essence rewritten every time it is read, because the of the text’s consumption changes its meaning – could not be truer of search queries.
The hunt for meaning in search now does not get underway when Google starts to hunt for resources to satisfy a query, but before with Google hunting for the meaning in the query itself.
Teodora Petkova: Aaron Bradley 🙂 I will have to work on the last paragraph to grasp it fully 🙂 Thanks for these thoughts.
The thing that is exciting is that before these texts weren’t as accessible. Plus accessible is only (mainly) accessible via search.
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