For example, I see everything in the context of "Smart City" ๐.
3/5
5. If you run an e-commerce ๐ website, you can analyze sessions by price and product category.
6. You can see what brand bring you the most visits.
(in both of these charts, the data from the KG is blended with data from #GoogleAnalytics)
4/5
Here is how it works:
1โฃ Add your @wordliftit key and write a query in GraphQL with the data points you need. The connector will access the KG and flatten the data into dimensions.
2โฃ Create a blend by matching the URL (products.urls ๐ Landing Page)
3โฃ Have fun!
5/5
โข โข โข
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๐งต ๐๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด๐ & ๐ฆ๐๐ข: A Powerful Multitool ๐ ๏ธ
In the world of #SEO, understanding and leveraging the power of #embeddings is a game-changer. But what are embeddings, and how do they work? Can we build our embeddings?
Let's dive in! #AI #Semantics
1/9
๐ช๐ต๐ฎ๐ ๐ฎ๐ฟ๐ฒ ๐ช๐ผ๐ฟ๐ฑ ๐๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด๐? ๐
Word embeddings are a type of word representation that allows words with similar meanings to have a similar representation in a multi-dimensional space. Using embeddings, we convert words into math (numerical vectors).
2/9
๐๐ผ๐ ๐ฑ๐ผ ๐๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด๐ ๐ช๐ผ๐ฟ๐ธ? ๐ง
Embeddings map words into a high-dimensional space where the distance and direction between words indicate their semantic relationship. Words with similar meanings are closer together, while different words are further apart.
3/9
1โฃ The latest 10 articles I wrote on the blog.
2โฃ My entity page (as *system message*).
3โฃThe article the user is reading.
4โฃA combination of the two indices above (a graph index).
I worked on my first experiment with ChatGPT Plugins applied to SEO! I created a search engine for an eCommerce site using WordLift's Product Knowledge Graph (PKG) as a starting point. Here is what I learned:
I have worked on automatic image captioning since 2019; recently, I have done a new analysis of the SOTA.
2/
I am generally less interested in models and more interested in finding the framework to fine-tune and evaluate models, so I found LAVIS by @salesforce, which provides access to 30 pre-trained and task-specific fine-tuned models checkpoints (ALBEF, BLIP, CLIP, and ALPRO).
3/
A small thread about Semantic SEO and #ChatGPT ๐ชก
As @SilviaKaya22 was testing @wordliftit new version of the SEO Add-on for Google Sheetsโข, she quickly compared @aleyda and me ๐ณ.
1/7
I feel like a newbie and an apprentice compared to Aleyda; nevertheless, the results grabbed my attention.
Using the new Add-on, we can compare search queries (and URLs) by looking at the entities behind top search results (or the entities behind single or multiple URLs).
2/7
We begin with two queries (Aleyda Solis and Andrea Volpini) and let the Add-on analyze the respective SERPs to highlight similarities and differences.
We both share, for example the entities:
- SEO (duh)
- entrepreneur (this also makes sense)