Continuous KNN Join Processing for Real-Time Recommendation -- 9
Budget: $30 – $250 AUD
What needs to be done in implementation:
1) The complete implementation of the HDR-Tree algorithm in mentioned paper using C++ language only which must include all the submodules(like PCA and Clustering, Dimensionality, Indexing, Construction, Updation, searching etc) of the HDR-Tree algorithm and it must produce the desired result if testing it with the MENTIONED DATASET in research papers.
2) Code should be well commented to understand the code flow. Entire implementation should be done as per the given paper only.
3) It should be designed considering the Text data input.
You can download the dataset from - https://lms.comp.nus.edu.sg/wp-content/uploads/2019/research/nuswide/NUS-WIDE.html
You need to test it with the Low-Level Features dataset from the above-mentioned link.
4) The algorithm should be implemented in a research paper-stated way.
The algorithm should be implemented as per the research paper stated way only.
1) The complete implementation of the HDR-Tree algorithm in mentioned paper using C++ language only which must include all the submodules(like PCA and Clustering, Dimensionality, Indexing, Construction, Updation, searching etc) of the HDR-Tree algorithm and it must produce the desired result if testing it with the MENTIONED DATASET in research papers.
2) Code should be well commented to understand the code flow. Entire implementation should be done as per the given paper only.
3) It should be designed considering the Text data input.
You can download the dataset from - https://lms.comp.nus.edu.sg/wp-content/uploads/2019/research/nuswide/NUS-WIDE.html
You need to test it with the Low-Level Features dataset from the above-mentioned link.
4) The algorithm should be implemented in a research paper-stated way.
The algorithm should be implemented as per the research paper stated way only.