acm-header
Sign In

Communications of the ACM

Blogroll


Refine your search:
datePast Year
authorDaniel Tunkelang
bg-corner

Quo Vadis Nunc, Quora?
From The Noisy Channel

Quo Vadis Nunc, Quora?

I was one of Quora’s earliest users, earned Top Writer status for a few years, and topped the leaderboard as a 9-time Knowledge Prize Winner. One of my answerswhere...

Seriously or Literally?
From The Noisy Channel

Seriously or Literally?

The other day, I posted about the need for search applications to take searchers seriously, not literally. This need holds even when searchers practically ask to...

Cold Start, Practical Edition
From The Noisy Channel

Cold Start, Practical Edition

If you are a search application developer or some other kind of machine learning practitioner, you have probably encountered a cold start problem: launching a data...

All Else Equal
From The Noisy Channel

All Else Equal

In The Three-Body Problem, Liu Cixin describes how an alien species drives scientists to suicide by making it impossible for them to produce consistent experimental...

Take Searchers Seriously, Not Literally
From The Noisy Channel

Take Searchers Seriously, Not Literally

Search application developers manage numerous tradeoffs, foremost the tradeoff between precision and recall. Precision measures the fraction of search results that...

Hallucinating a Post-Search World
From The Noisy Channel

Hallucinating a Post-Search World

When I first heard about 3D printing, I imagined something like a Star Trek replicator that could synthesize arbitrary objects — or at least meals — on demand.generative...

Handling Facets With Many Values
From The Noisy Channel

Handling Facets With Many Values

The previous post addresses the challenge of selecting which facets a search application should present to searchers as query refinements. However, there is another...

Facets, But Which Ones?
From The Noisy Channel

Facets, But Which Ones?

This post dives into a particular challenge of faceted search, exploring the challenge of selecting which facets a search application should present to searchers...

Searching for Discovery
From The Noisy Channel

Searching for Discovery

Search and DiscoveryIf search has one job, it is to help searchers find what they are looking for. However, many search application developers feel that searchHippocratic...

Where Do LTR Labels Come From?
From The Noisy Channel

Where Do LTR Labels Come From?

The most common goal that my search clients express is a desire to improve their ranking. I always start by managing their expectations and helping them understand...

How to be a Search Consultant
From The Noisy Channel

How to be a Search Consultant

If you have thought about hiring a search consultant or working as one, you may have asked yourself what exactly search consultants do. This post offers an opinionated...

Search and the Art of Conversation
From The Noisy Channel

Search and the Art of Conversation

What is the job of a search application? A common answer is that it needs to return the best results for a query, sorted in relevance order. While this answer sounds...

Is Search Trying Too Hard?
From The Noisy Channel

Is Search Trying Too Hard?

Last year, the emergence of ChatGPT and its ability to generate volumes from short prompts led me to speculate about the compressibility of thought. In a related...

Is Similarity Objective?
From The Noisy Channel

Is Similarity Objective?

Some search problems have binary answers. We often frame these problems in terms of matching or equivalence. A simplistic formulation of relevance is that a canonicalized...

Bags of Documents and the Cluster Hypothesis
From The Noisy Channel

Bags of Documents and the Cluster Hypothesis

My writing on AI-powered search promotes the “bag-of-documents” model, which represents a search query as a distribution of vectors for relevant documents. When...

Bags of Queries as Sparse Document Representations
From The Noisy Channel

Bags of Queries as Sparse Document Representations

There is a duality between search queries and indexed documents: we can model a query as a bag of documents and a document as a bag of queries. This duality offers...

Is Targeted Advertising Ethical
From The Noisy Channel

Is Targeted Advertising Ethical

Is Targeted Advertising Ethical?Targeted advertising is a huge industry with a massive branding problem. On one hand, nearly all of the “free” digital productspromoted...

Is Targeting Advertising Ethical?
From The Noisy Channel

Is Targeting Advertising Ethical?

Is Targeted Advertising Ethical?Targeted advertising is a huge industry with a massive branding problem. On one hand, nearly all of the “free” digital productspromoted...

Ranking vs. Relevance: 2 Pitfalls and How to Avoid Them
From The Noisy Channel

Ranking vs. Relevance: 2 Pitfalls and How to Avoid Them

A crucial distinction for search applications is the difference between ranking and relevance. In this post, I explain what happens when search applications fail...

Sparse and Dense Representations
From The Noisy Channel

Sparse and Dense Representations

The heart of the AI-powered search revolution is the move from sparse bag-of-words representations to dense embedding-based representations. But reducing everything...
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account