Searching Chinese Patents Presentation at Enterprise Data World
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War stories from building the Global Patent Search Network, and why Data folks need to think more about UX and Discovery, and UX folks need to think more about Data.
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Searching Chinese Patents Presentation at Enterprise Data World
- 1. Searching Chinese Patents: Challenges and Solutions When Building an Innovative Discovery Interface ERIC PUGH | epugh@o19s.com | @dep4b
- 2. Who am I? • Principal at OpenSource Connections - Solr/Lucene Search Consultancy http://bit.ly/OSCCommercialSummary • Member of Apache Software Foundation • SOLR-284 UpdateRichDocuments (July 07)
- 4. Agilista
- 8. Risks • Cloud new at USPTO • Discovery is tenuous concept • Conflicting User Goals • Fixed Budget: trade scope for budget/quality
- 14. Telling some stories ➡How to inject “Discovery” into your app • The Cloud to the Rescue (sorta!) • Parsers and Parsers and Parsers • Don’t be Afraid to Share!
- 15. Flow of understanding Data UnderstandingInformation
- 17. Grok data at gut level Look for outliers ! User Interviews Surveys Card Sorting Scenarios/Personas ! UX Data brainstorm Mockups Proof of concept ! !
- 18. Where to spend time? UX Engine Data 40% ! 20% ! 40% ! 40% ! 40% ! 20% We spent !
- 19. Telling some stories • How to inject “Discovery” into your app ➡The Cloud to the Rescue (sorta!) • Parsers and Parsers and Parsers • Don’t be Afraid to Share!
- 20. Boy meets Girl Story
- 21. Boy meets Girl Story Metadata Ingest Pipeline Discovery UX Content Files
- 22. How we built it EmberJS Single Page Search App HTML XML JSON Server Dashboard GPSN UI (Bootsrap CSS) Browsers Mobile/ Tablet Third Party Application Servers S3 BucketSolr
- 23. Solr as a NoSQL Datastore • Used “atomic updates” to merge three source datasets into single final dataset. • All text displayed in application stored in Solr. • Dynamic schema supports many languages, en, cn right now.
- 24. Lessons Learned
- 25. Don’t Move Files • Copying 5 TB data up to S3 was very painful. • We used S3Funnel which is “rsync like” • We bought more network bandwidth for our office
- 26. Never underestimate the bandwidth of a station wagon full of tapes hurtling down the highway. –Andrew Tanenbaum, 1981
- 27. Data Size 0 250000 500000 750000 1000000 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 Patent Count 277871
- 28. Think about DataVolume • Started with older dataset, and tasks like TIFF -> PNG conversion became progressively harder. Map/Reduce nice, need more visibility into progress.. • Should have sharded our Search Index from the beginning just to make indexing faster and cheaper process (500 gb index!) • 8 shards dropped time from 12 hours to 2 hours. Merging took 5! • We had too many steps in our pipeline
- 29. Building a Patents Index MachineCount 0 75 150 225 300 5 days 3 days 30 Minutes 1 5 300
- 30. Key scaling concept behind GPSN: ! Cloud meets Ocean
- 32. Telling some stories • How to inject “Discovery” into your app • The Cloud to the Rescue (sorta!) ➡Parsers and Parsers and Parsers • Don’t be Afraid to Share!
- 33. Why so many pipelines? Morphlines
- 34. Tika as a pipeline?
- 35. Lot’s of File Types • Sometimes in ZIP archives, sometimes not! • multiple XML formats as well as CSV and EDI • Purplebook,Yellowbook, Redbook,Greenbook, Questel, SIPO…
- 36. Tika as a pipeline! • Auto detects content type • Metadata structure has all the key/value needed for Solr • Allows us to scale up with Behemoth project (and others!).
- 37. Lots of files! HHHHHT APS1 ISSUE - 760106! PATN! WKU 039302717! SRC 5! APN 5328756! APT 1! ART 353! APD 19741216! TTL Golf glove! ISD 19760106! NCL 4! ECL 1 <PatentGrant>! <BibliographicData>! <GrantIdentification>! <DocumentKindCode>B1</DocumentKindCode>! <GrantNumber>06644224</GrantNumber>! <CountryCode>US</CountryCode>! <IssueDateText>2003-11-11</IssueDateText>
- 38. Detector to pick File public class GreenbookDetector implements Detector { ! private static Pattern pattern = Pattern.compile("PATN"); @Override public MediaType detect(InputStream stream, Metadata metadata) throws IOException { ! MediaType type = MediaType.OCTET_STREAM; InputStream lookahead = new LookaheadInputStream(stream, 1024); String extract = org.apache.commons.io.IOUtils.toString(lookahead, "UTF-‐8"); ! Matcher matcher = pattern.matcher(extract); ! if (matcher.find()) { type = GreenbookParser.MEDIA_TYPE; } ! lookahead.close(); return type; } }
- 39. Telling some stories • How to inject “Discovery” into your app • The Cloud to the Rescue (sorta!) • Parsers and Parsers and Parsers ➡Don’t be Afraid to Share!
- 40. Your BigData solution isn’t perfect • Allow users to export data • Most business users want to work in Excel. Accept it! • Allow other applications to build on top of of your application.
- 41. GPSN has • Lots of easy “Print to PDF” options. • Data stored in S3 as: • individual patent files • chunky downloads. • Filtering to expand or select specific data sets. • Permalinks: simple, very sharable URLs. • Underlying Solr service is exposed to public via proxy. You can query Solr yourself. • Need advance querying? Use Lucene syntax in search bar.
- 43. Measuring the impact of our algorithms changes is just getting harder with Big Data.
- 44. www.quepid.com Quepid: Give your Queries some Love W e need betausers!
- 45. Thank you! ! Questions? • epugh@o19s.com • @dep4b • www.opensourceconnections.com • slideshare.com/o19s Nervous about speaking up? Ask me later!