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Crowd-DB - Answering Queries with Crowdsourcing
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Lecture Structure
- I IF Rnrknlsm (00:00:01)
- L Is1 (00:00:44)
- Today s appsi sz fixed point in solution space Algorithms (00:02:18)
- Carried uver ham RADLahlETH Algorithms (00:04:25)
- Algorithms (00:06:37)
- I Comuanv Name Add ress Market Ca Google Googleplex Nltn View CA 210Bn (00:06:46)
- SELECT Market CapFI OI I COmpZ 1l Ü ESWh I COIT paI 1y Na T1 = (00:07:17)
- SELECT Market Cap (00:07:01)
- From Companies (00:07:01)
- IBM (00:07:01)
- where (00:07:01)
- COmpElI 1y NElm (00:07:01)
- I Comuanv Name Address Market Ca Google Googleplax Mtn View CA 210Bn (00:07:41)
- rx? EHC (00:08:09)
- I Comuanv Name Add ress Market Cap Google Googleplax Mtn View CA 210Bn (00:08:32)
- I Comuanv Name Add rass Market Ca Google Googleplax Mtn View CA 210Bn (00:10:11)
- amazon mechanicalturw Anificial Artificial Intelliuance (00:10:32)
- U13 fu amaxuunneclmvuucm tuvk (00:12:14)
- m xonn1e h 1uv 1Iruvk (00:13:48)
- SOL Result (00:13:51)
- SQL Result (00:14:02)
- Cr0wdSQL Result (00:14:34)
- LJ LJ? (00:17:03)
- DDL Extensions Crowdsourced columns Crowdsourced tables (00:17:26)
- DDL Extensions Crowdsourced columns Cm wdsourced tables (00:17:46)
- Closed World Open World (00:18:08)
- rnwhm r (00:21:15)
- CREATE CROWD TABLE department Vlam STRING PRIMARY KEY SELECT (00:24:52)
- O vv awve C 1vey (00:25:08)
- Rule based optimizer (00:25:27)
- New technique to deal with open wor d assumption (00:25:27)
- Simple heuristics to set the crowd parameters (00:25:27)
- SELECT O r ame Ca1ey (00:26:45)
- SELECT G name Ca1ey (00:27:59)
- LJU (00:28:29)
- O name? Carey (00:28:29)
- VN Onamev 1 T Cavsyi (00:28:29)
- T X M pGE d namef gw (00:28:29)
- Ä66 (00:28:29)
- Current Focus PK Queries es FI TÄ I SELECT O name? Car y (00:30:05)
- Olm (00:30:40)
- Creates user interface templates and selects ph (00:30:40)
- physical (00:30:40)
- operators (00:30:40)
- l 3 new crowd operators use the templates to collect the (00:30:40)
- data from the crowd (00:30:40)
- V name Lamy1 oooo D 1 m 1 v oOProfessor Department (00:30:05)
- J Pnmy supported f lg A (00:30:05)
- I LIIVIII U LU Prolessor Depanmem II Professor oepanmem I FjJ u l k ää SELECT T Only allowed mom Paorsssoa p M @ m I Q r @ a F DEPARTMENTI1 GO O0 Impmvemem I WHERE pdep Z dmme Pmressm uepanmem I 435 (00:30:05)
- CrowdProbe Crowdloin CrowdFunction (00:31:12)
- 1 Prepares request by initiating the user interface templates (00:35:25)
- HITS (00:36:00)
- Crowd Tables (00:35:25)
- Headq uaner (00:35:25)
- bmi (00:35:25)
- Phone (00:35:25)
- Dwanmem lv (00:35:25)
- Currently Simple Quorum Vote (00:36:52)
- Currently Simple Quorum Vote Carey (00:37:06)
- E 1rv r rrx EAU (00:38:14)
- Schema Data Snze CREATE TABLE company Big BLUE 100 company names (00:40:58)
- A cost based optimizer for the crowd (00:41:48)
- ä But not when looked at from an hourly wage perspective I would do (00:43:57)
- lg work for this reguester again posted byi (00:43:57)
- zu 2an Emc E (00:42:16)
- Time mins (00:42:16)
- O r ame Care (00:45:35)
- Iul (00:47:07)
- 1rn (00:50:55)
- Data Model Query Languages User mtcrfaccs Extansuons Autumanc UI gen ratmn (00:51:40)
- Nsw crowdsuurcmg platform (00:51:40)
- Worker Imaage (00:51:40)
- Storage Cachmg (00:51:40)
- Hybnd Machmc Leammg Human A g0nthm (00:51:40)
- Worker Ralatuonshup Nlanagaman (00:51:40)
- Quality Control (00:51:40)
- Query Execution (00:51:40)
- Eauhmg (00:51:40)
- Query Optimization (00:51:40)
- New sort om algonthms Algcnthms (00:51:40)
- lT 313 3 (00:52:18)
- Sturaga Caching (00:52:18)
- Qualitv Control (00:52:18)
- Multhwav vs bmaw cowvarvson (00:52:18)
- Query Optimization (00:52:18)
- New sun juin algorithms Algorithms (00:52:18)
- Data Collection (00:52:52)
- g yV Ql ULl mr Tr1 L L (00:56:35)
- DBMS optimizes queries (00:56:35)
- The DB Approach (00:56:35)
- Learning effects Community Management (00:56:35)
- Jungle uf different techniques (00:56:35)
- Changing platform behavior (00:56:35)
- Many many knubs to tum (00:56:35)
- Why not? (00:56:35)
- Programming Language GUI (00:56:35)
- Q 4 I JJÄAIQAI lsou (00:57:23)
- wwcls r r Wr1s1 L (00:57:32)
- Crom d c Jr inY Äpfpglieatingns anH P a rfBrrr s?A Öatä Mana engent Perspective (00:57:32)
- Crovgdgoor in gy t ms on he Worl Wide W i7 ACM Communications 2011 (00:57:32)
- Ovenriew Tutorials (00:57:32)
- Crowdsourced Databases Query Processing with People C DR 2011 (00:57:32)
- MIT Qurk (00:57:32)
- Why not? (00:57:32)
- The AI IPLab looks into integrating Algorithms Machines and People for big data ana ytics v (00:57:33)
- Stanford Deco A Parameswaran and N Polvzotisz (00:57:35)
- The AI IPLab looks into integrating Algorithms Machines and People for big data anaiytics r (00:58:50)
Keyword
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