Is Search Broken?! Daniel Tunkelang Chief Scientist, Endeca

howdy! 1992: Bachelor’s + Master’s from MIT in CS + Math 1998: PhD from CMU in CS (ACO program) 1999: Co-founded Endeca! 2008: ???

1992: Bachelor’s + Master’s from MIT in CS + Math

1998: PhD from CMU in CS (ACO program)

1999: Co-founded Endeca!

2008: ???

overview Who is Endeca? Is search broken? If it is, what can we do about it?

Who is Endeca?

Is search broken?

If it is, what can we do about it?

who / what is endeca? Software to help people explore, analyze, and understand complex information, guiding them to unexpected insights and better decisions. 500+ customers $108M revenue in 2007.

Software to help people explore, analyze, and understand complex information, guiding them to unexpected insights and better decisions.

500+ customers

$108M revenue in 2007.

some of our customers

Is search broken?

Is search broken?

Search has hit a wall.

Search has hit a wall.

search hits a wall in ecommerce

search hits a wall in knowledge management Current Search: it outsourcing

search even hits a wall on the web Results 1-10 out of about 344,000,000 for ir

But is search broken?

But is search broken?

the accountants don’t think so

most users don’t think so 75

or do they? 78% wish search engines could read their minds. What frustrates users most? 25%: deluge of results 24%: too many paid listings 19%: inability to understand their keywords 19%: disorganized / random results The State of Search Autobytel & Kelton Research, Oct ’07

78% wish search engines could read their minds.

What frustrates users most?

25%: deluge of results

24%: too many paid listings

19%: inability to understand their keywords

19%: disorganized / random results

The State of Search

Autobytel & Kelton Research, Oct ’07

web search vs. enterprise search “ Search on the internet is solved. I always find what I need. But why not in the enterprise? Seems like a solution waiting to happen.” - a Fortune 500 CTO

“ Search on the internet is solved. I always find what I need. But why not in the enterprise? Seems like a solution waiting to happen.”

- a Fortune 500 CTO

Can theory help?

Can theory help?

precision = fraction of retrieved documents that are relevant recall = fraction of relevant documents that are retrieved retrieved documents relevant documents

why improve precision? the truth, nothing but the truth

why improve recall? the whole truth,

what we want… the truth, the whole truth, nothing but the truth

but there is a trade-off… recall precision

which should we favor? Precision …to avoid annoying users with irrelevant results? Recall …to make sure we don’t throw away results the user wants / needs?

Enough stalling…what’s the answer?!

Enough stalling…what’s the answer?!

depends on what you want vs.

you get what you pay for There are easy use cases… 30% of queries are navigational. 30% of queries lead to Wikipedia pages. Users won’t pay, but advertisers will! …and hard use cases. Queries where recall matters. Exploratory search. Enterprises will pay for insight.

There are easy use cases…

30% of queries are navigational.

30% of queries lead to Wikipedia pages.

Users won’t pay, but advertisers will!

…and hard use cases.

Queries where recall matters.

Exploratory search.

Enterprises will pay for insight.

Great, bring on the insight!

Great, bring on the insight!

technology alone can’t provide insight The system can’t read your mind. Your spouse / best friend can’t read your mind. Sometimes you can’t read your own mind.

The system can’t read your mind.

Your spouse / best friend can’t read your mind.

Sometimes you can’t read your own mind.

So should we just give up?

So should we just give up?

technology is a catalyst Computers are good at analysis. People are good at using what they know. How do we get the best of both worlds?

Computers are good at analysis.

People are good at using what they know.

How do we get the best of both worlds?

with apologies to luis von ahn

human-computer information retrieval Instead of guessing the user’s intent, optimize communication. De-emphasize the top ten documents; response is a set of documents. Think beyond single queries; support refinement and exploration.

Instead of guessing the user’s intent, optimize communication.

De-emphasize the top ten documents; response is a set of documents.

Think beyond single queries; support refinement and exploration.

hcir cheats the trade-off recall precision

But how do we implement HCIR?

But how do we implement HCIR?

endeca's approach: guided summarization Set retrieval that responds to queries with an overview of the user's current context. an organized set of options for incremental exploration. Contextual summaries of document sets optimize system’s communication with user. Query refinement options optimize user’s communication with system.

Set retrieval that responds to queries with

an overview of the user's current context.

an organized set of options for incremental exploration.

Contextual summaries of document sets optimize system’s communication with user.

Query refinement options optimize user’s communication with system.

guided summarization for ecommerce Matching Categories include: Appliances > Small Appliances > Irons & Steamers Appliances > Small Appliances > Microwaves & Steamers Bath > Sauna & Spas > Steamers Kitchen > Bakeware & Cookware > Cookware > Open Stock Pots > Double Boilers & Steamers Kitchen > Small Appliances > Steamers

Matching Categories include:

Appliances > Small Appliances > Irons & Steamers

Appliances > Small Appliances > Microwaves & Steamers

Bath > Sauna & Spas > Steamers

Kitchen > Bakeware & Cookware > Cookware >

Open Stock Pots > Double Boilers & Steamers

Kitchen > Small Appliances > Steamers

guided summarization for KM

Guided summarization starts with faceted search.

Guided summarization starts with faceted search.

facets 101

But faceted search isn’t enough…

But faceted search isn’t enough…

showing the right facets: microwaves vs.

showing the right facets: ceiling fans

traditional topic taxonomy

dynamic topic facet Subject Electronic data processing (1002) Distributed processing (937) Parallel processing (619) Computer networks (562) Fault-tolerant-computing (365) Show more… Subject Artificial intelligence (227) High performance computing (244) Automatic theorem proving (9) History (11) Client/server computing (185) Information technology (145) Computer algorithms (110) Java (77) Computer architecture (162) Law and legislation (70) Computer networks (552) Logic, Symbolic and mathematical (16) Computer programs (139) Mathematics (70) Computer security (151) Mobile communication systems (54) Computer software (253) Operating systems (87) Computers (124) Parallel processing (619) Database management (277) Research (83) Distributed processing (937) Software engineering (197) Electronic data processing (1002) Supercomputers (139) Electronic digital computers (148) Web databases (54) Fault-tolerant computing (365) Wireless communication systems (97)

Subject

Electronic data processing (1002)

Distributed processing (937)

Parallel processing (619)

Computer networks (562)

Fault-tolerant-computing (365)

Show more…

facets populated using entity extraction apple production

cutting through facets to show the big picture Search : storage

summarization: more than search and browse

guided summarization – a summary Guided summarization enables a dialog between the user and the data, enabling exploration and discovery.

Guided summarization enables a dialog

between the user and the data,

enabling exploration and discovery.

The Moral

The Moral

think outside the box Search works for many use cases. But not for some of the most valuable ones. Focus on human-computer information retrieval.

Search works for many use cases.

But not for some of the most valuable ones.

Focus on human-computer information retrieval.

One More Thing

One More Thing

maybe we should treat search as a game

thank you Questions?

Questions?