🤔 What’s Multi-Token Search?

When people say multi-token search, they usually mean a search made up of multiple tokens, regardless of whether those tokens are full words or parts of words.

• In practical terms, multi-token search ≈ multi-word search — it's what happens when you type more than one word into a search box.

• The system looks for text that contains all those tokens, but they don’t need to be right next to each other or in order.

📘 Example:

Example 1: Literal Match

You search for: heart disease treatment

It might match:

“Treatment options for chronic disease, especially those affecting the heart, are expanding rapidly.”

Here, all the words are explicitly present:

• “treatment”

• “disease”

• “heart”

They aren’t adjacent, but the system still considers it a match because all the tokens appear somewhere in the text.

📘 Example 2: Conceptual Relevance Match

You search for the same term: heart disease treatment

It might also match:

“Common approaches to managing cardiovascular conditions include lifestyle changes, cholesterol-lowering medications, blood pressure control, and surgical interventions such as stent placement or bypass surgery.”

This time:

• “heart” is implied through “cardiovascular”

• “disease” is expressed as “conditions”

• “treatment” is reflected through specific interventions, like medications, surgery, and lifestyle changes

Even though the exact phrase “heart disease treatment” never appears, this passage is highly relevant — it's essentially a list of treatment options for heart disease, using more domain-specific terms.

This is where multi-token or proximity search becomes especially powerful: it captures conceptual relevance, not just literal overlap.

🎯 When to Use It:

✅ Use multi-token (or proximity) search when you're more interested in conceptual relevance than exact wording — especially in:

• Clinical notes or patient summaries

• Scientific article abstracts

• Health policy documents or public health briefs

• News stories or commentary

It’s ideal when you want to surface meaningfully related content, even if it's described using different language.

🧵 How Is That Different from Phrase Search?

Phrase search is more strict. It looks for the exact sequence of tokens you typed, in the same order, and right next to each other.

• It’s like using quotation marks — you're asking for that precise phrase and nothing less.

• If the words are rearranged, or other words are inserted between them, it won't match.

📘 Example:

You search for: "heart disease treatment"

This will only match:

“A new heart disease treatment was approved by the FDA.”

But it will not match:

“A treatment for disease affecting the heart…”

— because even though all the words are present, they’re not in the exact order.

🎯 When to Use It:

✅ Use phrase search when you're looking for tight, specific language, such as:

• Exact quotations

• Technical phrases (e.g., "climate change", "artificial intelligence")

• Brand or product names

• Specific event names or known terms