SlideShare ist ein Scribd-Unternehmen logo

probabilistic ranking

•Als PPT, PDF herunterladen•
•
F
FELIX75
Technologie
1 von 50
Supporting Ranking in Queries Score-based Paradigm Russell Greenspan CS 411 Spring 2004
Supporting Ranking in Queries Talk Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Ranking in Queries What is ranking in queries? ,[object Object],[object Object],[object Object],[object Object],[object Object]
What is ranking in queries? Definitions ,[object Object],[object Object],[object Object],[object Object]
What is ranking in queries? Differences from traditional queries ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ranking in Queries Why use ranking in queries? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ranking in Queries How do we use execute ranked queries? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How do we use execute ranked queries? “Smart” Ranked Query Execution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Smart” Ranked Query Execution Two Areas of Research Focus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Smart” Ranked Query Execution Research and Techniques ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Smart” Ranked Querying (Middleware) – Garlic [Fagin, 1999] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Garlic [Fagin, 1999] Rank Processing Methods ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Garlic [Fagin, 1999] Example Query ,[object Object],.4 H .7 G .1 F .9 E .2 D .3 C .8 B .6 A Roundness Object .3 H .9 G .5 F .3 E .8 D .1 C .6 B .2 A Redness Object
Garlic [Fagin, 1999] Inefficient vs. Efficient Processing ,[object Object],[object Object],[object Object],[object Object],[object Object],.12 H .63 G .05 F .27 E .16 D .03 C .48 B .12 A Score Object
Garlic [Fagin, 1999] Inefficient vs. Efficient Processing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Garlic [Fagin, 1999] Conclusions ,[object Object],[object Object],[object Object]
“ Smart” Ranked Querying (Middleware) – CHITRA [Nepal, Ramakrishna, 1999] ,[object Object],[object Object]
CHITRA [Nepal, Ramakrishna, 1999] “Multi-step” Algorithm ,[object Object],[object Object],[object Object],[object Object]
CHITRA [Nepal, Ramakrishna, 1999] Example Query ,[object Object],.4 H .7 G .1 F .9 E .2 D .3 C .8 B .6 A Roundness Object .3 H .9 G .5 F .3 E .8 D .1 C .6 B .2 A Redness Object
CHITRA [Nepal, Ramakrishna, 1999] Example Scoring Functions Results ,[object Object],[object Object],[object Object],B = min[.6, .8] = .6 G = min[.7, .9] = .7 D = min[.8, .2] = .2 B = min[.8, .6] = .6 G = min[.9, .7] = .7 E = min[.9, .3] = .3 Grade {G, B} min[.6, .7] = .6 i1 = {B(.6)} i2 = {G(.7)} 3 min[.8, .8] = .8 i1 = {D(.8)} i2 = {B(.8)} 2 min[.9, .9] = .9 i1 = {G(.9)} i2 = {E(.9)} 1 Resultset Threshold Items Iter. B = [.6 * .8] = .48 G = [.7 * .9] = .63 D = [.8 * .2] = .16 B = [.8 * .6] = .48 G = [.9 * .7] = .63 E = [.9 * .3] = .27 Grade {G, B} [.6 * .7] = .43 i1 = {B(.6)} i2 = {G(.7)} 3 [.8 * .8] = .64 i1 = {D(.8)} i2 = {B(.8)} 2 [.9 * .9] = .81 i1 = {G(.9)} i2 = {E(.9)} 1 Resultset Threshold Items Iter.
CHITRA [Nepal, Ramakrishna, 1999] Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Smart” Ranked Querying (Relational) – STOP Operator [Carey, et al, 1997] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
STOP Operator [Carey, et al, 1997] Example query plans ,[object Object],[object Object],[object Object],[object Object]
STOP Operator [Carey, et al, 1997] Conservative Heuristic ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
STOP Operator [Carey, et al, 1997] Aggressive Heuristic ,[object Object],[object Object],[object Object]
STOP Operator [Carey, et al, 1997] Experimental Results ,[object Object],[object Object],[object Object],18.5 sec 63.1 sec 63.9 sec 128.3 sec Aggressive, Overestimate (10) Aggressive, Underestimate (1/10) Conservative Traditional
STOP Operator [Carey, et al, 1997] Experimental Results ,[object Object]
“ Smart” Ranked Querying (Relational) – Probabilistic [Donjerkovic, et al, 1999] ,[object Object],[object Object],[object Object]
Probabilistic [Donjerkovic, et al, 1999] Comparison with STOP Operator ,[object Object]
Probabilistic [Donjerkovic, et al, 1999] Implementation ,[object Object],[object Object],[object Object]
Probabilistic [Donjerkovic, et al, 1999] Performance ,[object Object],[object Object]
“ Smart” Ranked Querying (Relational) – Statistical [Chaudhuri, Gravano, 1999] ,[object Object],[object Object],[object Object]
Statistical [Chaudhuri, Gravano, 1999] Expansion of probabilistic model ,[object Object],[object Object],[object Object],[object Object]
Statistical [Chaudhuri, Gravano, 1999] Implementation ,[object Object],[object Object]
Statistical [Chaudhuri, Gravano, 1999] Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Statistical [Chaudhuri, Gravano, 1999] Expansion of Fagin’s model ,[object Object],[object Object],[object Object]
“ Smart” Ranked Querying (Rank) – MPro [Chang, Hwang, 2002] ,[object Object],[object Object],[object Object],[object Object]
MPro [Chang, Hwang, 2002] Determining if probe is necessary ,[object Object],[object Object],[object Object],[object Object],[object Object]
MPro [Chang, Hwang, 2002] Determining all necessary probes ,[object Object],[object Object],[object Object]
MPro [Chang, Hwang, 2002] Minimal Probes Algorithm (MPro) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MPro [Chang, Hwang, 2002] Further Applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MPro [Chang, Hwang, 2002] Experimental Results ,[object Object],[object Object]
“ Smart” Ranked Querying (Rank) – AutoRank [Agrawal, et al, 2003] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
AutoRank [Agrawal, et al, 2003] IDF Similarity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
AutoRank [Agrawal, et al, 2003] Q F Similarity ,[object Object],[object Object],[object Object],[object Object],[object Object]
AutoRank [Agrawal, et al, 2003] Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
AutoRank [Agrawal, et al, 2003] Experimental Results ,[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object]
The Future ,[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Empfohlen

CS 542 -- Query Optimization
CS 542 -- Query OptimizationCS 542 -- Query Optimization
CS 542 -- Query OptimizationJ Singh
 
Af4201214217
Af4201214217Af4201214217
Af4201214217IJERA Editor
 
Distributed Query Processing
Distributed Query ProcessingDistributed Query Processing
Distributed Query ProcessingMythili Kannan
 
Query-porcessing-& Query optimization
Query-porcessing-& Query optimizationQuery-porcessing-& Query optimization
Query-porcessing-& Query optimizationSaranya Natarajan
 
Kmeans
KmeansKmeans
KmeansNikita Goyal
 
assia2015sakai
assia2015sakaiassia2015sakai
assia2015sakaiTetsuya Sakai
 
Lp and ip programming cp 9
Lp and ip programming cp 9Lp and ip programming cp 9
Lp and ip programming cp 9M S Prasad
 
Query compiler
Query compilerQuery compiler
Query compilerDigvijay Singh
 

Empfohlen

CS 542 -- Query Optimization
CS 542 -- Query OptimizationCS 542 -- Query Optimization
CS 542 -- Query OptimizationJ Singh
 
Af4201214217
Af4201214217Af4201214217
Af4201214217IJERA Editor
 
Distributed Query Processing
Distributed Query ProcessingDistributed Query Processing
Distributed Query ProcessingMythili Kannan
 
Query-porcessing-& Query optimization
Query-porcessing-& Query optimizationQuery-porcessing-& Query optimization
Query-porcessing-& Query optimizationSaranya Natarajan
 
Kmeans
KmeansKmeans
KmeansNikita Goyal
 
assia2015sakai
assia2015sakaiassia2015sakai
assia2015sakaiTetsuya Sakai
 
Lp and ip programming cp 9
Lp and ip programming cp 9Lp and ip programming cp 9
Lp and ip programming cp 9M S Prasad
 
Query compiler
Query compilerQuery compiler
Query compilerDigvijay Singh
 
Mixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. GrossmannMixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. GrossmannCAChemE
 
Query optimisation
Query optimisationQuery optimisation
Query optimisationWBUTTUTORIALS
 
Ip3514921495
Ip3514921495Ip3514921495
Ip3514921495IJERA Editor
 
Balanced trees
Balanced trees Balanced trees
Balanced trees meet darji
 
Deep Feature Synthesis
Deep Feature SynthesisDeep Feature Synthesis
Deep Feature SynthesisMartin Eastwood
 
Study on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining SortStudy on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining SortIRJET Journal
 
Chapter15
Chapter15Chapter15
Chapter15gourab87
 
Overview of query evaluation
Overview of query evaluationOverview of query evaluation
Overview of query evaluationavniS
 
Top-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with PrioritiesTop-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with Prioritiesijtsrd
 
K-Means Algorithm Implementation In python
K-Means Algorithm Implementation In pythonK-Means Algorithm Implementation In python
K-Means Algorithm Implementation In pythonAfzal Ahmad
 
Branch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear ProgrammingBranch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear ProgrammingKaivalya Shah
 
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer SelectionSeoul National University
 
K means clustering | K Means ++
K means clustering | K Means ++K means clustering | K Means ++
K means clustering | K Means ++sabbirantor
 
Taguchi introduction concept 1
Taguchi introduction concept 1Taguchi introduction concept 1
Taguchi introduction concept 1Sliet2017
 
Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21Hyun Wong Choi
 
Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design Dan Elton
 
Scp final
Scp finalScp final
Scp finalFingerfast Laboratory
 
Seabank exterior
Seabank exteriorSeabank exterior
Seabank exteriorseabank
 
2012 WTR Club OPP
2012 WTR Club OPP2012 WTR Club OPP
2012 WTR Club OPPwaytorich
 
Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2ABPI
 
Energy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity StudioEnergy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity StudioBiocity Studio
 
Real Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May GarlandReal Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May Garlandrealestatehistory
 

Weitere ähnliche Inhalte

Was ist angesagt?

Mixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. GrossmannMixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. GrossmannCAChemE
 
Balanced trees
Balanced trees Balanced trees
Balanced trees meet darji
 
Study on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining SortStudy on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining SortIRJET Journal
 
Overview of query evaluation
Overview of query evaluationOverview of query evaluation
Overview of query evaluationavniS
 
Top-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with PrioritiesTop-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with Prioritiesijtsrd
 
K-Means Algorithm Implementation In python
K-Means Algorithm Implementation In pythonK-Means Algorithm Implementation In python
K-Means Algorithm Implementation In pythonAfzal Ahmad
 
Branch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear ProgrammingBranch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear ProgrammingKaivalya Shah
 
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer SelectionSeoul National University
 
K means clustering | K Means ++
K means clustering | K Means ++K means clustering | K Means ++
K means clustering | K Means ++sabbirantor
 
Taguchi introduction concept 1
Taguchi introduction concept 1Taguchi introduction concept 1
Taguchi introduction concept 1Sliet2017
 
Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21Hyun Wong Choi
 
Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design Dan Elton
 

Was ist angesagt? (16)

Mixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. GrossmannMixed-integer and Disjunctive Programming - Ignacio E. Grossmann
Mixed-integer and Disjunctive Programming - Ignacio E. Grossmann
 
Query optimisation
Query optimisationQuery optimisation
Query optimisation
 
Ip3514921495
Ip3514921495Ip3514921495
Ip3514921495
 
Balanced trees
Balanced trees Balanced trees
Balanced trees
 
Deep Feature Synthesis
Deep Feature SynthesisDeep Feature Synthesis
Deep Feature Synthesis
 
Study on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining SortStudy on Sorting Algorithm and Position Determining Sort
Study on Sorting Algorithm and Position Determining Sort
 
Chapter15
Chapter15Chapter15
Chapter15
 
Overview of query evaluation
Overview of query evaluationOverview of query evaluation
Overview of query evaluation
 
Top-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with PrioritiesTop-K Dominating Queries on Incomplete Data with Priorities
Top-K Dominating Queries on Incomplete Data with Priorities
 
K-Means Algorithm Implementation In python
K-Means Algorithm Implementation In pythonK-Means Algorithm Implementation In python
K-Means Algorithm Implementation In python
 
Branch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear ProgrammingBranch and Bound technique to solve Integer Linear Programming
Branch and Bound technique to solve Integer Linear Programming
 
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
[poster] A Compare-Aggregate Model with Latent Clustering for Answer Selection
 
K means clustering | K Means ++
K means clustering | K Means ++K means clustering | K Means ++
K means clustering | K Means ++
 
Taguchi introduction concept 1
Taguchi introduction concept 1Taguchi introduction concept 1
Taguchi introduction concept 1
 
Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21Final edited master defense-hyun_wong choi_2019_05_23_rev21
Final edited master defense-hyun_wong choi_2019_05_23_rev21
 
Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design Introduction to Reinforcement Learning for Molecular Design
Introduction to Reinforcement Learning for Molecular Design
 

Andere mochten auch

Seabank exterior
Seabank exteriorSeabank exterior
Seabank exteriorseabank
 
2012 WTR Club OPP
2012 WTR Club OPP2012 WTR Club OPP
2012 WTR Club OPPwaytorich
 
Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2ABPI
 
Energy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity StudioEnergy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity StudioBiocity Studio
 
Real Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May GarlandReal Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May Garlandrealestatehistory
 
Presentationwithmusic
PresentationwithmusicPresentationwithmusic
Presentationwithmusicguest05d6d3a
 
Photos In Every Day Of Lif3
Photos In Every Day Of Lif3Photos In Every Day Of Lif3
Photos In Every Day Of Lif3byanca16
 
Развитие бизнеса: менеджмент проектов и управление коллективом
Развитие бизнеса: менеджмент проектов и управление коллективомРазвитие бизнеса: менеджмент проектов и управление коллективом
Развитие бизнеса: менеджмент проектов и управление коллективомIngria. Technopark St. Petersburg
 
When Data Gets Up Close and Personal
When Data Gets Up Close and PersonalWhen Data Gets Up Close and Personal
When Data Gets Up Close and PersonalStephen Anderson
 
Personal public private social security saving accounts
Personal public private social security saving accounts Personal public private social security saving accounts
Personal public private social security saving accounts Matias Zelikowicz
 

Andere mochten auch (20)

Scp final
Scp finalScp final
Scp final
 
Seabank exterior
Seabank exteriorSeabank exterior
Seabank exterior
 
2012 WTR Club OPP
2012 WTR Club OPP2012 WTR Club OPP
2012 WTR Club OPP
 
Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2Andrew Powrie Smith Breakdowns V2
Andrew Powrie Smith Breakdowns V2
 
Energy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity StudioEnergy and Sydney - high demand and new solutions | Biocity Studio
Energy and Sydney - high demand and new solutions | Biocity Studio
 
Real Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May GarlandReal Estate The Basis Of All Wealth William May Garland
Real Estate The Basis Of All Wealth William May Garland
 
Presentationwithmusic
PresentationwithmusicPresentationwithmusic
Presentationwithmusic
 
NHS Points 10-26-09
NHS Points 10-26-09NHS Points 10-26-09
NHS Points 10-26-09
 
Presentation5 2
Presentation5 2Presentation5 2
Presentation5 2
 
Брендинг стартапов
Брендинг стартаповБрендинг стартапов
Брендинг стартапов
 
Poem Namin Lahat
Poem Namin LahatPoem Namin Lahat
Poem Namin Lahat
 
Photos In Every Day Of Lif3
Photos In Every Day Of Lif3Photos In Every Day Of Lif3
Photos In Every Day Of Lif3
 
Portraits
PortraitsPortraits
Portraits
 
Zombie Survival
Zombie SurvivalZombie Survival
Zombie Survival
 
Newsboy
NewsboyNewsboy
Newsboy
 
Qualification - Scotsman
Qualification - ScotsmanQualification - Scotsman
Qualification - Scotsman
 
Pocket School
Pocket SchoolPocket School
Pocket School
 
Развитие бизнеса: менеджмент проектов и управление коллективом
Развитие бизнеса: менеджмент проектов и управление коллективомРазвитие бизнеса: менеджмент проектов и управление коллективом
Развитие бизнеса: менеджмент проектов и управление коллективом
 
When Data Gets Up Close and Personal
When Data Gets Up Close and PersonalWhen Data Gets Up Close and Personal
When Data Gets Up Close and Personal
 
Personal public private social security saving accounts
Personal public private social security saving accounts Personal public private social security saving accounts
Personal public private social security saving accounts
 

Ähnlich wie probabilistic ranking

Part 1
Part 1Part 1
Part 1butest
 
iccv2009 tutorial: boosting and random forest - part III
iccv2009 tutorial: boosting and random forest - part IIIiccv2009 tutorial: boosting and random forest - part III
iccv2009 tutorial: boosting and random forest - part IIIzukun
 
Analytics Boot Camp - Slides
Analytics Boot Camp - SlidesAnalytics Boot Camp - Slides
Analytics Boot Camp - SlidesAditya Joshi
 
Silicon valleycodecamp2013
Silicon valleycodecamp2013Silicon valleycodecamp2013
Silicon valleycodecamp2013Sanjeev Mishra
 
learned optimizer.pptx
learned optimizer.pptxlearned optimizer.pptx
learned optimizer.pptxQingsong Guo
 
Gradient Boosted Regression Trees in scikit-learn
Gradient Boosted Regression Trees in scikit-learnGradient Boosted Regression Trees in scikit-learn
Gradient Boosted Regression Trees in scikit-learnDataRobot
 
Functional Programming in Swift
Functional Programming in SwiftFunctional Programming in Swift
Functional Programming in SwiftSaugat Gautam
 
Interactively querying Google Analytics reports from R using ganalytics
Interactively querying Google Analytics reports from R using ganalyticsInteractively querying Google Analytics reports from R using ganalytics
Interactively querying Google Analytics reports from R using ganalyticsJohann de Boer
 
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...PyData
 
Lecture21-Query-Optimization-1April-2018.pptx
Lecture21-Query-Optimization-1April-2018.pptxLecture21-Query-Optimization-1April-2018.pptx
Lecture21-Query-Optimization-1April-2018.pptxRishabMishra25
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic rankingFELIX75
 
Asymptotic Analysis
Asymptotic AnalysisAsymptotic Analysis
Asymptotic Analysissonugupta
 
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLE
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLEUnit 3 - Function & Grouping,Joins and Set Operations in ORACLE
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLEDrkhanchanaR
 
Coursera 1week
Coursera 1weekCoursera 1week
Coursera 1weekcsl9496
 

Ähnlich wie probabilistic ranking (20)

Part 1
Part 1Part 1
Part 1
 
iccv2009 tutorial: boosting and random forest - part III
iccv2009 tutorial: boosting and random forest - part IIIiccv2009 tutorial: boosting and random forest - part III
iccv2009 tutorial: boosting and random forest - part III
 
9-Query Processing-05-06-2023.PPT
9-Query Processing-05-06-2023.PPT9-Query Processing-05-06-2023.PPT
9-Query Processing-05-06-2023.PPT
 
Analytics Boot Camp - Slides
Analytics Boot Camp - SlidesAnalytics Boot Camp - Slides
Analytics Boot Camp - Slides
 
Silicon valleycodecamp2013
Silicon valleycodecamp2013Silicon valleycodecamp2013
Silicon valleycodecamp2013
 
learned optimizer.pptx
learned optimizer.pptxlearned optimizer.pptx
learned optimizer.pptx
 
Sorting_project_2.pdf
Sorting_project_2.pdfSorting_project_2.pdf
Sorting_project_2.pdf
 
Gradient Boosted Regression Trees in scikit-learn
Gradient Boosted Regression Trees in scikit-learnGradient Boosted Regression Trees in scikit-learn
Gradient Boosted Regression Trees in scikit-learn
 
Functional Programming in Swift
Functional Programming in SwiftFunctional Programming in Swift
Functional Programming in Swift
 
Lecture4.pptx
Lecture4.pptxLecture4.pptx
Lecture4.pptx
 
Planet
PlanetPlanet
Planet
 
Lect4
Lect4Lect4
Lect4
 
Interactively querying Google Analytics reports from R using ganalytics
Interactively querying Google Analytics reports from R using ganalyticsInteractively querying Google Analytics reports from R using ganalytics
Interactively querying Google Analytics reports from R using ganalytics
 
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...
Gradient Boosted Regression Trees in Scikit Learn by Gilles Louppe & Peter Pr...
 
Lecture21-Query-Optimization-1April-2018.pptx
Lecture21-Query-Optimization-1April-2018.pptxLecture21-Query-Optimization-1April-2018.pptx
Lecture21-Query-Optimization-1April-2018.pptx
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic ranking
 
Asymptotic Analysis
Asymptotic AnalysisAsymptotic Analysis
Asymptotic Analysis
 
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLE
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLEUnit 3 - Function & Grouping,Joins and Set Operations in ORACLE
Unit 3 - Function & Grouping,Joins and Set Operations in ORACLE
 
Lec13 Clustering.pptx
Lec13 Clustering.pptxLec13 Clustering.pptx
Lec13 Clustering.pptx
 
Coursera 1week
Coursera 1weekCoursera 1week
Coursera 1week
 

Mehr von FELIX75

technorati
technoratitechnorati
technoratiFELIX75
 
technorati
technoratitechnorati
technoratiFELIX75
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic rankingFELIX75
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic rankingFELIX75
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic rankingFELIX75
 
DB-IR-ranking
DB-IR-rankingDB-IR-ranking
DB-IR-rankingFELIX75
 
IR-ranking
IR-rankingIR-ranking
IR-rankingFELIX75
 

Mehr von FELIX75 (8)

technorati
technoratitechnorati
technorati
 
technorati
technoratitechnorati
technorati
 
php
phpphp
php
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic ranking
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic ranking
 
probabilistic ranking
probabilistic rankingprobabilistic ranking
probabilistic ranking
 
DB-IR-ranking
DB-IR-rankingDB-IR-ranking
DB-IR-ranking
 
IR-ranking
IR-rankingIR-ranking
IR-ranking
 

Kürzlich hochgeladen

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilV3cube
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...gurkirankumar98700
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 

Kürzlich hochgeladen (20)

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 

probabilistic ranking

  • 1. Supporting Ranking in Queries Score-based Paradigm Russell Greenspan CS 411 Spring 2004
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48.
  • 49.
  • 50.