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Information Retrieval
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Quest for Efficient AI: An Evaluation of the Vector Database Landscape
Earlier this year, due to soaring interest and multiple product initiatives, we went on a quest to evaluate and deploy an internally hosted vector database. We’re in the midst of the AI revolution, and many new AI‑inspired product initiatives rely on vector embeddings. Embeddings are generated by AI models, and take the form of high dimensional…
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Real-Time Elasticsearch Indexing on WordPress.com
Love databases, indexing, and Elasticsearch gymnastics? Greg Brown walks us through the indexing sausage factory on WordPress.com.
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Improving Relevance and Elasticsearch Query Patterns
The WordPress.org plugin directory has been significantly rebuilt over the past year and should go live soon (test site). Many from across the WordPress community helped with this effort. I focused on improving plugin search relevancy. This was a great learning experience on how to build more relevant searches for a couple of reasons: There…
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Intro to Search: Measurement
Welcome to the third part of our mini-series “Intro to Search.” In my previous posts, I’ve discussed the characteristics of great search results and what a search engine looks like from the inside. But, how do we know if our algorithms actually deliver relevant search results? The answer is, of course, by measurement! There is…
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Intro to Search: Anatomy of a search engine
Welcome to the second post in our “Intro to Search”-series! Today, we’ll dig into the building blocks of search engines to give you an idea of just how we identify what posts to show readers using WordPress.com’s search tool. A (web) search engine connects users with relevant documents. This process generally has five main stages:…
Data for Breakfast 