personalized news recommendation based on twitter user modeling
TRANSCRIPT
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Personalized News
Recommendation System with Different
User Modeling
Engineers: Mahesh Attarde (201205685) Arpita Raj Gupta (201101121) Pankhuri Goyal (201101174)
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Problem
INFORMATION OVERLOAD
Understand “Me”
Recommend news that “Interest”
Me!
Use Social My “Social
Behavior”
Learn Me over “Time”
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Problem
INFORMATION OVERLOAD
Understand “Me”
Recommend news that “Interest”
Me!
Use Social My “Social
Behavior”
Learn Me over “Time”
Personalized News Recommendation
![Page 4: Personalized News Recommendation based on Twitter User Modeling](https://reader036.vdocuments.mx/reader036/viewer/2022082218/558b9e4fd8b42a5b5b8b45bd/html5/thumbnails/4.jpg)
Social Feed -> Web
Tweet Processing
Enrichment
User Analysis User Models
URL enrichment
Topic/Entity Enrichment
Entity/HashTag/Topic Identification
Temporal Classification
Personalized
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Challenge 1
• Design of User Model
[across million attributes and users]
• Design Similarity of Users
User Model
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Challenge 2
• Design of Recommendation
[filtering across million attributes and users]
• Design ranking in user attributes [topic, entity, hash tag ]
Recommendation
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User Model -> Rec Engine
• Temporal Feature
• Profile Types
• Enrichment Types
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Prototype – What we had
• Twitter 7.6 GB corpus
• Over 1.2 years
• 1218 users with avg.
of 175 tweets per user
• News corpus of 75,000+ articles
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Prototype – What we Found
• Hash Tags distinct 100000+
• Topics - distinct 18 types
• Entities – distinct 39 types
Temporal Feature of Hash Tag
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Prototype – our Play
• User Profiles
1)Hash Tag Profile
2)Entity Profile
3)Topic Profile
4)Experimental enriched
• Recommendation Engine cosine similarity based
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Results
• Hash tag profiles grow quickly and last for period [Used Weka-Excel]
• Entity and Topic Profiles suggest relevant
suggestions
• Enrichment in Topics and Entity help to correctly judge “subject”
<Improved Profile>
TEMPORAL EFFECT
PROFILE EFFECT
Enrichment EFFECT
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Snap Shots
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Snap Shots
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Snap Shots
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Snap Shots
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Tools and Lib
• Weka
• Excel
• Open Cailais
• Stanford NPL lib
• Apache Mahout
• RDBMS -mysql
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Thank You !
Professor Vasudev Varma
Aishvarya Singh
Guided By
Mentored By