SlideShare une entreprise Scribd logo

12/18 regular meeting paper

•
•
M
marxliouville

The document proposes a framework to use social network data and transaction records to identify cohesive customer subgroups for targeted advertising. It defines a cohesion measure to identify subgroups where customers have strong social ties. Transaction data is used to estimate each product category's "liking" for each subgroup. A linear program then selects the optimal set of customers from high-liking subgroups to target for a given product. The approach was evaluated on a university library circulation dataset and outperformed random advertising.

Technologie
1  sur  32
Mining Social Network for Targeted Advertising ,[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object]
The problem ,[object Object],[object Object],[object Object]
The problem ,[object Object],[object Object],[object Object]
The problem ,[object Object],[object Object]
The problem ,[object Object],[object Object]
The problem ,[object Object],[object Object],[object Object]
Mining cohesive subgroups from social network ,[object Object]
Mining cohesive subgroups from social network ,[object Object]
Mining cohesive subgroups from social network ,[object Object]
Mining cohesive subgroups from social network ,[object Object],[object Object]
Mining cohesive subgroups from social network ,[object Object]
Mining cohesive subgroups from social network ,[object Object],[object Object],[object Object]
Mining cohesive subgroups from social network
Mining cohesive subgroups from social network ,[object Object],[object Object],[object Object]
Targeted advertising based on cohesive subgroups ,[object Object],[object Object],[object Object]
Targeted advertising based on cohesive subgroups ,[object Object]
Targeted advertising based on cohesive subgroups ,[object Object]
Targeted advertising based on cohesive subgroups ,[object Object],[object Object]
Evaluation ,[object Object],[object Object],[object Object],[object Object]
Evaluation ,[object Object],[object Object],[object Object]
Evaluation
Evaluation
Evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation
Related work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conclusion ,[object Object],[object Object],[object Object],[object Object]

Recommandé

FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
IJDKP
 
A novel recommender for mobile telecom alert services - linkedin
A novel recommender for mobile telecom alert services - linkedinA novel recommender for mobile telecom alert services - linkedin
A novel recommender for mobile telecom alert services - linkedin
Asoka Korale
 
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
Editor IJCATR
 
An Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
An Adaptive Framework for Enhancing Recommendation Using Hybrid TechniqueAn Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
An Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
ijcsit
 
T0 numtq0njc=
T0 numtq0njc=T0 numtq0njc=
T0 numtq0njc=
International Journal of Science and Research (IJSR)
 
Behavioral targeting
Behavioral targetingBehavioral targeting
Behavioral targeting
Avelin Huo
 
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
Journal For Research
 
Online brand Communities as Networks Engagement and Reach
Online brand Communities as Networks Engagement and ReachOnline brand Communities as Networks Engagement and Reach
Online brand Communities as Networks Engagement and Reach
Scott Sanders
 

Recommandé

FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
FHCC: A SOFT HIERARCHICAL CLUSTERING APPROACH FOR COLLABORATIVE FILTERING REC...
IJDKP
 
A novel recommender for mobile telecom alert services - linkedin
A novel recommender for mobile telecom alert services - linkedinA novel recommender for mobile telecom alert services - linkedin
A novel recommender for mobile telecom alert services - linkedin
Asoka Korale
 
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
A Hybrid Approach for Personalized Recommender System Using Weighted TFIDF on...
Editor IJCATR
 
An Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
An Adaptive Framework for Enhancing Recommendation Using Hybrid TechniqueAn Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
An Adaptive Framework for Enhancing Recommendation Using Hybrid Technique
ijcsit
 
T0 numtq0njc=
T0 numtq0njc=T0 numtq0njc=
T0 numtq0njc=
International Journal of Science and Research (IJSR)
 
Behavioral targeting
Behavioral targetingBehavioral targeting
Behavioral targeting
Avelin Huo
 
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
A REVIEW PAPER ON BFO AND PSO BASED MOVIE RECOMMENDATION SYSTEM | J4RV4I1015
Journal For Research
 
Online brand Communities as Networks Engagement and Reach
Online brand Communities as Networks Engagement and ReachOnline brand Communities as Networks Engagement and Reach
Online brand Communities as Networks Engagement and Reach
Scott Sanders
 
A Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender SystemA Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender System
theijes
 
Report
ReportReport
Report
Manpreet Singh
 
IRJET- Analysis of Rating Difference and User Interest
IRJET- Analysis of Rating Difference and User InterestIRJET- Analysis of Rating Difference and User Interest
IRJET- Analysis of Rating Difference and User Interest
IRJET Journal
 
B1802021823
B1802021823B1802021823
B1802021823
IOSR Journals
 
FIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation SystemFIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation System
IJTET Journal
 
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
IRJET Journal
 
Ccr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online datingCcr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online dating
Sean Chiu
 
An Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder TechniqueAn Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder Technique
IJCSIS Research Publications
 
20
2020
20
Technology_solution
 
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.comHABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
HABIB FIGA GUYE
 
Introduction to Recommendation Systems
Introduction to Recommendation SystemsIntroduction to Recommendation Systems
Introduction to Recommendation Systems
Zia Babar
 
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
IJMTST Journal
 
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDYSIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
Journal For Research
 
my model genuines.
my model genuines.my model genuines.
my model genuines.
Teng Xiaolu
 
Ontological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systemsOntological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systems
vikramadityajakkula
 
IJSRED-V2I2P09
IJSRED-V2I2P09IJSRED-V2I2P09
IJSRED-V2I2P09
IJSRED
 
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
HossamSharara
 
Adaptive Search Based On User Tags in Social Networking
Adaptive Search Based On User Tags in Social NetworkingAdaptive Search Based On User Tags in Social Networking
Adaptive Search Based On User Tags in Social Networking
IOSR Journals
 
A Recommender System Sensitive to Intransitive Choice and Preference Reversals
A Recommender System Sensitive to Intransitive Choice and Preference ReversalsA Recommender System Sensitive to Intransitive Choice and Preference Reversals
A Recommender System Sensitive to Intransitive Choice and Preference Reversals
csandit
 
Recommendation Systems Basics
Recommendation Systems BasicsRecommendation Systems Basics
Recommendation Systems Basics
Jarin Tasnim Khan
 
Simply Data driven behavioural algorithms
Simply Data driven behavioural algorithmsSimply Data driven behavioural algorithms
Simply Data driven behavioural algorithms
Nana Bianca
 
Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3
Dave King
 

Contenu connexe

Tendances

A Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender SystemA Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender System
theijes
 
FIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation SystemFIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation System
IJTET Journal
 
Ccr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online datingCcr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online dating
Sean Chiu
 
An Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder TechniqueAn Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder Technique
IJCSIS Research Publications
 
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
IJMTST Journal
 
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDYSIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
Journal For Research
 
my model genuines.
my model genuines.my model genuines.
my model genuines.
Teng Xiaolu
 
Ontological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systemsOntological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systems
vikramadityajakkula
 
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
HossamSharara
 

Tendances (19)

A Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender SystemA Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender System
 
Report
ReportReport
Report
 
IRJET- Analysis of Rating Difference and User Interest
IRJET- Analysis of Rating Difference and User InterestIRJET- Analysis of Rating Difference and User Interest
IRJET- Analysis of Rating Difference and User Interest
 
B1802021823
B1802021823B1802021823
B1802021823
 
FIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation SystemFIND MY VENUE: Content & Review Based Location Recommendation System
FIND MY VENUE: Content & Review Based Location Recommendation System
 
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...
 
Ccr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online datingCcr a content collaborative reciprocal recommender for online dating
Ccr a content collaborative reciprocal recommender for online dating
 
An Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder TechniqueAn Efficient Trust Evaluation using Fact-Finder Technique
An Efficient Trust Evaluation using Fact-Finder Technique
 
20
2020
20
 
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.comHABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
HABIB FIGA GUYE {BULE HORA UNIVERSITY}(habibifiga@gmail.com
 
Introduction to Recommendation Systems
Introduction to Recommendation SystemsIntroduction to Recommendation Systems
Introduction to Recommendation Systems
 
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
Effective Cross-Domain Collaborative Filtering using Temporal Domain – A Brie...
 
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDYSIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDY
 
my model genuines.
my model genuines.my model genuines.
my model genuines.
 
Ontological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systemsOntological and clustering approach for content based recommendation systems
Ontological and clustering approach for content based recommendation systems
 
IJSRED-V2I2P09
IJSRED-V2I2P09IJSRED-V2I2P09
IJSRED-V2I2P09
 
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
Differential Adaptive Diffusion: Understanding Diversity and Learning whom to...
 
Adaptive Search Based On User Tags in Social Networking
Adaptive Search Based On User Tags in Social NetworkingAdaptive Search Based On User Tags in Social Networking
Adaptive Search Based On User Tags in Social Networking
 
A Recommender System Sensitive to Intransitive Choice and Preference Reversals
A Recommender System Sensitive to Intransitive Choice and Preference ReversalsA Recommender System Sensitive to Intransitive Choice and Preference Reversals
A Recommender System Sensitive to Intransitive Choice and Preference Reversals
 

Similaire à 12/18 regular meeting paper

Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3
Dave King
 
Fuzzy Logic Based Recommender System
Fuzzy Logic Based Recommender SystemFuzzy Logic Based Recommender System
Fuzzy Logic Based Recommender System
RSIS International
 
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
IJTET Journal
 
Data-driven Reserve Prices for Social Advertising Auctions at LinkedIn
Data-driven Reserve Prices for Social Advertising Auctions at LinkedInData-driven Reserve Prices for Social Advertising Auctions at LinkedIn
Data-driven Reserve Prices for Social Advertising Auctions at LinkedIn
Kun Liu
 
Recommender System _Module 1_Introduction to Recommender System.pptx
Recommender System _Module 1_Introduction to Recommender System.pptxRecommender System _Module 1_Introduction to Recommender System.pptx
Recommender System _Module 1_Introduction to Recommender System.pptx
Satyam Sharma
 
A Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender SystemA Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender System
theijes
 
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETINGA GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
IJDKP
 

Similaire à 12/18 regular meeting paper (20)

Recommendation Systems Basics
Recommendation Systems BasicsRecommendation Systems Basics
Recommendation Systems Basics
 
Simply Data driven behavioural algorithms
Simply Data driven behavioural algorithmsSimply Data driven behavioural algorithms
Simply Data driven behavioural algorithms
 
Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3Digital Trails Dave King 1 5 10 Part 2 D3
Digital Trails Dave King 1 5 10 Part 2 D3
 
IRJET- Hybrid Book Recommendation System
IRJET- Hybrid Book Recommendation SystemIRJET- Hybrid Book Recommendation System
IRJET- Hybrid Book Recommendation System
 
Fuzzy Logic Based Recommender System
Fuzzy Logic Based Recommender SystemFuzzy Logic Based Recommender System
Fuzzy Logic Based Recommender System
 
Collaborative Filtering Recommendation System
Collaborative Filtering Recommendation SystemCollaborative Filtering Recommendation System
Collaborative Filtering Recommendation System
 
MINING COMPETITORS FROM LARGE UNSTRUCTURED DATASETS
MINING COMPETITORS FROM LARGE UNSTRUCTURED DATASETSMINING COMPETITORS FROM LARGE UNSTRUCTURED DATASETS
MINING COMPETITORS FROM LARGE UNSTRUCTURED DATASETS
 
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...
 
IMPROVING COLLABORATIVE RECOMMENDATION VIA USER-ITEM SUBGROUPS
IMPROVING COLLABORATIVE RECOMMENDATION VIA USER-ITEM SUBGROUPSIMPROVING COLLABORATIVE RECOMMENDATION VIA USER-ITEM SUBGROUPS
IMPROVING COLLABORATIVE RECOMMENDATION VIA USER-ITEM SUBGROUPS
 
Advances In Collaborative Filtering
Advances In Collaborative FilteringAdvances In Collaborative Filtering
Advances In Collaborative Filtering
 
Data-driven Reserve Prices for Social Advertising Auctions at LinkedIn
Data-driven Reserve Prices for Social Advertising Auctions at LinkedInData-driven Reserve Prices for Social Advertising Auctions at LinkedIn
Data-driven Reserve Prices for Social Advertising Auctions at LinkedIn
 
Connecting social media to e commerce (2)
Connecting social media to e commerce (2)Connecting social media to e commerce (2)
Connecting social media to e commerce (2)
 
Recommender System _Module 1_Introduction to Recommender System.pptx
Recommender System _Module 1_Introduction to Recommender System.pptxRecommender System _Module 1_Introduction to Recommender System.pptx
Recommender System _Module 1_Introduction to Recommender System.pptx
 
Recommender systems in indian e-commerce context
Recommender systems in indian e-commerce contextRecommender systems in indian e-commerce context
Recommender systems in indian e-commerce context
 
A Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender SystemA Study of Neural Network Learning-Based Recommender System
A Study of Neural Network Learning-Based Recommender System
 
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETINGA GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
A GRAPH BASED APPROACH FOR EFFECTIVE INFLUENCER MARKETING
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and Development
 
A1060104
A1060104A1060104
A1060104
 
International Journal of Engineering Research and Development
International Journal of Engineering Research and DevelopmentInternational Journal of Engineering Research and Development
International Journal of Engineering Research and Development
 
A1060104
A1060104A1060104
A1060104
 

Plus de marxliouville

The Problem of Peer Node Recognition
The Problem of Peer Node RecognitionThe Problem of Peer Node Recognition
The Problem of Peer Node Recognition
marxliouville
 
1212 regular meeting
1212 regular meeting1212 regular meeting
1212 regular meeting
marxliouville
 
20080919 regular meeting報告
20080919 regular meeting報告20080919 regular meeting報告
20080919 regular meeting報告
marxliouville
 
0902 regular meeting
0902 regular meeting0902 regular meeting
0902 regular meeting
marxliouville
 
04/29 regular meeting paper
04/29 regular meeting paper04/29 regular meeting paper
04/29 regular meeting paper
marxliouville
 
04/29 regular meeting paper
04/29 regular meeting paper04/29 regular meeting paper
04/29 regular meeting paper
marxliouville
 
2/19 regular meeting paper
2/19 regular meeting paper2/19 regular meeting paper
2/19 regular meeting paper
marxliouville
 

Plus de marxliouville (14)

20090813MEETING
20090813MEETING20090813MEETING
20090813MEETING
 
20091006meeting
20091006meeting20091006meeting
20091006meeting
 
The Problem of Peer Node Recognition
The Problem of Peer Node RecognitionThe Problem of Peer Node Recognition
The Problem of Peer Node Recognition
 
FivaTech
FivaTechFivaTech
FivaTech
 
1212 regular meeting
1212 regular meeting1212 regular meeting
1212 regular meeting
 
20081009 meeting
20081009 meeting20081009 meeting
20081009 meeting
 
20080919 regular meeting報告
20080919 regular meeting報告20080919 regular meeting報告
20080919 regular meeting報告
 
0902 regular meeting
0902 regular meeting0902 regular meeting
0902 regular meeting
 
04/29 regular meeting paper
04/29 regular meeting paper04/29 regular meeting paper
04/29 regular meeting paper
 
04/29 regular meeting paper
04/29 regular meeting paper04/29 regular meeting paper
04/29 regular meeting paper
 
2/19 regular meeting paper
2/19 regular meeting paper2/19 regular meeting paper
2/19 regular meeting paper
 
10/23 paper
10/23 paper10/23 paper
10/23 paper
 
1023 paper
1023 paper1023 paper
1023 paper
 
A+Novel+Approach+Based+On+Prototypes+And+Rough+Sets+For+Document+And+Feature+...
A+Novel+Approach+Based+On+Prototypes+And+Rough+Sets+For+Document+And+Feature+...A+Novel+Approach+Based+On+Prototypes+And+Rough+Sets+For+Document+And+Feature+...
A+Novel+Approach+Based+On+Prototypes+And+Rough+Sets+For+Document+And+Feature+...
 

Dernier

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMECloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
sammart93
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 

Dernier (20)

AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMECloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelNavi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
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
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 

12/18 regular meeting paper