© 2008 endeca technologies, inc. all rights reserved. is search broken?! daniel tunkelang chief...

© 2008 Endeca Technologies, Inc. All rights reserved.

Is Search Broken?!

Daniel TunkelangChief Scientist, Endeca

© 2008 Endeca Technologies, Inc. All rights reserved.2

howdy!

• 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 / 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.


some of our customers


Is search broken?


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?


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 SearchAutobytel & 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


Can theory help?


precision = fraction of retrieved documents that are relevant

recall = fraction of relevant documents that are retrieved

retrieveddocuments

relevantdocuments


the truth,

nothing but the truth

why improve precision?


the whole truth,

why improve recall?


the truth,the whole truth, nothing but the

truth

what we want…


recall

precision

but there is a trade-off…


Precision…to avoid annoying users with irrelevant results?

which should we favor?

Recall…to make sure we don’t throw away results the user wants / needs?


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.


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.


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?


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.


recall

precision

hcir cheats the trade-off


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.


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


guided summarization for KM


Guided summarization starts withfaceted search.


facets 101


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…

SubjectArtificial 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)


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 dialogbetween the user and the data,

enabling exploration and discovery.


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.


One More Thing


maybe we should treat search as a game


thank you

Questions?

© 2008 endeca technologies, inc. all rights reserved. is search broken?! daniel tunkelang chief...

Documents

endeca technologies

endeca slide

founded endeca

ahn slide

ecommerce slide

cto slide

ir slide

enterprise search search