1 / 0

Hugh E. Williams Vice President, Experience, Search, and Platforms @ hughewilliams , hugh@hughwilliams.com

Challenges in Commerce Search. Hugh E. Williams Vice President, Experience, Search, and Platforms @ hughewilliams , hugh@hughwilliams.com. eBay Today. 50+ petabytes. Of data in our Hadoop and Teradata clusters. 2+ billion . 250 million. Page views each day. 75+ billion.

soren
Télécharger la présentation

Hugh E. Williams Vice President, Experience, Search, and Platforms @ hughewilliams , hugh@hughwilliams.com

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Challenges in Commerce Search

    Hugh E. WilliamsVice President, Experience, Search, and Platforms@hughewilliams, hugh@hughwilliams.com

  2. eBay Today
  3. 50+ petabytes Of data in our Hadoop and Teradata clusters 2+ billion 250 million Page views each day 75+ billion Database calls each day Queries per day
  4. Commerce $10 trillion The opportunity ahead is huge Online Commerce $1 trillion Source: Economist Intelligence Unit, Morgan Stanley Note: Market sizes as of 2012, Compounded Annual Growth Rates from 2012 to 2015
  5. Today’s Search Turnaround contributor Series of improvements Ten year old technology
  6. Conversionup 13% Better Search 2010 Simple Flows Better Images Merch’ing Other 2012
  7. Improving Search from 2009 to 2012 User experience changes Imagery Reorganization Optimization Major page refresh Speed Search science Query understanding and rewriting Understanding user intent Behavioral measurement Substantial ranking improvements (particularly to Fixed Price ranking) And all on a 10+ year old platform named Voyager
  8. Query Understanding and Rewriting Our search engine was literal We’re on a journey to make it more intuitive Idea: Mine our query-session data, look for patterns, and use these to map words in user queries to synonyms and structured data User Query Search Query Search Query Rewrite eBay Results
  9. PATTERNS: QUERY REWRITES … pilzlampe
  10. How do buyers purchase the pilzlampe? It turns out, they do one of a few things: Type pilzlampe, and purchase Type pilzlampe, … , pilzlampe, and purchase Type pilzlampe, … , pilzlampen, and purchase Type pilzlampen, … , pilzlampe, and purchase …
  11. How do buyers purchase the pilzlampe? From our data mining: We automatically discover that pilzlampeand pilzlampeare the same We also discover that pilzand pilzeare the same, and lampeand lampenare the same From these patterns, we rewrite the user’s query pilzlampeas: pilzlampeOR “pilzlampe” OR “pilzlampen” OR pilzlampen OR “pilzelampe” OR pilzelampe OR “pilzelampen” OR pilzelampen
  12. Are Query Rewrites easy? Nothing is easy at scale Incorrect strong signals: CMU is not Central Michigan University Mariners is not the same as Marines Context matters Correcting Seattle Marines to Seattle Mariners is (generally) right Denver Nuggets is not Denver in the Jewelry & Watches category
  13. Next Gen Search An even bigger opportunity
  14. Cassini: Reengineering eBay Search

  15. Top-to-Bottom View
  16. How hard is it to ship a new search engine? Voyager is used for much more than the obvious. It’s multi-tenant: “Default Search” search (already migrated to Cassini in the US) Completed, null and low (already migrated to Cassini worldwide) Description search Deterministic sorts Query rewrite Merchandizing The Feed Selling (for example, allowing sellers to create listings from similar items) Category browsing Motors and other verticals Many fast “item lookup” scenarios for other teams Many scenarios we don’t even know about…
  17. What’s else is hard about eBay search? eBay has over 400 million items listed in multiple languages Our collection of items changes fast You can find just about anything on eBay. We have to optimize for every type of item Not everybody follows the same listing practices, or uses the same keywords or units Examples include: Units of measure: centimeter versus cm, gigabytesversus gb Colors: Blue versus Aqua, Rojois the same as Red Synonyms: laptopand notebook, mobile phone and cell phone Abbreviations: SGA means Stadium Giveaway Spelling errors Our goal is to help both buyers and sellers find items even when they use different ways of expressing the same things
  18. Technology Deep dive: Infrastructure What’s hard at eBay? Multi-tenant system Document additions and deletions Document modifications Index updates Result caching Data center automation …
  19. Technology Deep dive: Ranking What’s hard at eBay? Mix of items: good ’til canceled multi quantity vs. single quantity Gaps in catalog data A very different problem: different ranking signals to Web search The deterministic sort: Recall versus precision Consistency with best match Spam Result blending
  20. But What Comes Next?
  21. 44% 21% of eBay multiscreenusers of GMV share
  22. Q&A?
More Related