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dateMore Than a Year Ago
authorDaniel Tunkelang
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Using AI to Understand Search Intent
From The Noisy Channel

Using AI to Understand Search Intent

Several weeks ago, I wrote a post advocating the use of AI for query understanding. I argued that holistic query understanding with embeddings and deep learning...

The Eternal Quest for Meaning
From The Noisy Channel

The Eternal Quest for Meaning

In 1668, John Wilkins published An Essay Towards a Real Character, and a Philosophical Language. In it, he proposed a universal language that would represent every...

Ranking vs. Relevance
From The Noisy Channel

Ranking vs. Relevance

Most folks who work on search worry about relevance. But it’s surprisingly difficult to find a useful definition of relevance.Defining RelevanceMerriam-Webster ...

Putting Search Ranking in Perspective
From The Noisy Channel

Putting Search Ranking in Perspective

For feeds and recommendations, ranking is critical. All the inputs are implicit, so machine-learned ranking is the only practical way to optimize engagement.Search...

New Choice
From The Noisy Channel

New Choice

In improv, there’s a fun game called “new choice”. At any point during the improvised scene, the host can call for a “new choice”. The player who last spoke has...

AI for Query Understanding
From The Noisy Channel

AI for Query Understanding

In the past decade, the incredible progress in word embeddings and deep learning has fueled an interest in neural information retrieval. An increasing number of...

Query Understanding
From The Noisy Channel

Query Understanding

This publication is a series of posts devoted to query understanding. Each post is self-contained, but there is a natural progression. If you’d like to read them...

Recall: Size Isn’t Everything
From The Noisy Channel

Recall: Size Isn’t Everything

Recall is a key measure of search quality that doesn’t always get the attention it deserves. But how does a search engine recognize when recall is a problem?Size...

The 3 Rs of Search: Relevance, Recall, and Ranking
From The Noisy Channel

The 3 Rs of Search: Relevance, Recall, and Ranking

In grade school, we were taught the three Rs: reading, writing, and ‘rithmetic. In search, we can be thankful that the three Rs actually start with the letter R...

In Search of Recall
From The Noisy Channel

In Search of Recall

Search developers tend to focus most of their efforts on the first page of results. As a result, they prioritize investment in ranking models, with the goal ofprecision...

Putting Users Back In Control
From The Noisy Channel

Putting Users Back In Control

Francis Fukuyama, Barak Richman, and Ashish Goel recently published a piece in Foreign Affairs, which they ambitiously titled “How to Save Democracy From Technology...

Facets of Faceted Search
From The Noisy Channel

Facets of Faceted Search

Faceted search is a fascinating topic. It’s a standard feature of site search, and one could write an entire book on the subject. In this post, I’ll focus on some...

Expanding on Explore-Exploit
From The Noisy Channel

Expanding on Explore-Exploit

A few years ago, I proposed a non-adversarial ad-supported model: an explore-exploit model, applicable to search engines and feeds, that aligns the interests of...

Wolf, thank you for these additional points.
From The Noisy Channel

Wolf, thank you for these additional points.

Wolf, thank you for these additional points. I agree that Peter Norvig’s post, while very educational, is a starting point to learn about spelling correction but...

Coffee, Coffee, Coffee!
From The Noisy Channel

Coffee, Coffee, Coffee!

In 1984, Robin Williams starred in Moscow on the Hudson as a Russian saxophonist who decides to defect from the USSR during a shopping trip to a New York department...

Learning from Friction to Improve the Search Experience
From The Noisy Channel

Learning from Friction to Improve the Search Experience

When we design search applications, we aspire to make the user experience frictionless. A search engine should “just work”, enabling searchers to easily express...

Thanks. And sorry that slide was cryptically brief.
From The Noisy Channel

Thanks. And sorry that slide was cryptically brief.

Thanks. And sorry that slide was cryptically brief. What I mean is that spelling correction should not restrict itself to correcting each token separately. Many...

In this case, I’m imagining that the only match of the string “black” against one of the attributes…
From The Noisy Channel

In this case, I’m imagining that the only match of the string “black” against one of the attributes…

In this case, I’m imagining that the only match of the string “black” against one of the attributes is for the “color” attribute. If the string matches multiple...

The typical integration approach I’ve seen is to use a separate query rewriting service that then…
From The Noisy Channel

The typical integration approach I’ve seen is to use a separate query rewriting service that then…

The typical integration approach I’ve seen is to use a separate query rewriting service that then either filter the Solr query to the preferred categories / attributes...

If the results for two queries expressing the same intent are similar, then they should map to…
From The Noisy Channel

If the results for two queries expressing the same intent are similar, then they should map to…

If the results for two queries expressing the same intent are similar, then they should map to similar vectors. If not, then it’s more complicated. You might still...
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