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Hans Behrens, , 25% Yash Garg, , 25% Prad Kadambi, , 25%

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Presentation on theme: "Hans Behrens, , 25% Yash Garg, , 25% Prad Kadambi, , 25%"— Presentation transcript:

1 CSE 575 Class Project Presentation Dynamic Tag Recommendation In High-Dimensional Systems
Hans Behrens, , 25% Yash Garg, , 25% Prad Kadambi, , 25% Yanyao Wang, , 25%

2 Presentation Overview
Ourselves Our Goals Our Motivations Our Methods Our Findings

3 Dynamic Tag Recommendation In High-Dimensional Systems
Our Goals (1/4) Dynamic Tag Recommendation In High-Dimensional Systems

4 Dynamic Tag Recommendation In High-Dimensional Systems
Our Goals (2/4) Dynamic Tag Recommendation In High-Dimensional Systems

5 Dynamic Tag Recommendation In High-Dimensional Systems
Our Goals (3/4) Dynamic Tag Recommendation In High-Dimensional Systems

6 Dynamic Tag Recommendation In High-Dimensional Systems
Our Goals (4/4) Dynamic Tag Recommendation In High-Dimensional Systems

7 Our Motivations (1/3) Practical Performance Relevancy Kernelizable
Incrementally Updateable Relevancy Recommender Systems Neural Networks

8 Our Motivations (2/3) Useful To Users To Developers
Improve ability to find relevant posts Get help faster To Developers Evaluate possibilities Highlight successes & failures

9 Our Motivations (3/3) Challenging Dimensionality Scale
75K unique words 47K unique tags Scale 50GB dataset 1 million posts

10 Our Methods (1/8) Dataset Preprocessing
Data Cleaning Stop Words Numbers Tyops <HTML>

11 Our Methods (2/8) Characteristic Extraction
Weight Matrix

12 Our Methods (3/8) Modelling
Tensor Decomposition CC-BY-SA-3.0

13 Our Methods (4/8) Modelling
Neural Network (Convolutional)

14 Our Methods (5/8) Modelling
SVM

15 Our Methods (6/8) Modelling
Neural Network (Perceptron)

16 Our Methods (7/8) Modelling
Neural Network (Multi-Layer Perceptron) Hidden Layers Input Layer Output Layer 𝑥 𝑛 𝑦

17 Our Methods (8/8) Modelling
Ensemble Learning Max Pooling Averaging

18 Our Findings (1/1) [ Precision & Recall results will be included in the written report ]

19 Q&A Session

20 This page intentionally left blank

21 Team Information All the team members agree on the team members’ contributions, in terms of both (a) what they did and (b) the percentage. Hans Behrens, , 25% Project proposal, project report, project presentation & slides Python/RDBMS integration; data cleaning & representation brainstorming Yash Garg, , 25% Network and ensemble modeling Prad Kadambi, , 25% Explored GPU acceleration and integration, Django web UI, convolutional neural networks Yanyao Wang, , 25% Explored TF-IDF

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