# Intro


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## IDP Theme
IDP Theme： Developing a Literature Research Tool that Automatically Search Literature and Summarize the Research Trends.

## Objective
In this IDP, we are going to develop a literature research tool that enables three functionalities:
1. Automatically search the most recent literature filtered by keywords on three literature platforms: Elvsier, IEEE and Google Scholar
2. Automatically summarize the most popular research directions and trends in  the searched literature from step 1
3. visualize the results from step 1 and step 2


## Timeline & Milestones & Tasks
![](https://i.imgur.com/mDK0sc0.png)

#### Tasks
| Label   | Start      | End        | Duration | Description                                                                                              |
| ------- |------------| ---------- |----------| -------------------------------------------------------------------------------------------------------- |
| Task #1 | 15/11/2022 | 15/12/2022 | 30 days  | Implement literature search by keywords on three literature platforms: Elvsier, IEEE, and Google Scholar |
| Task #2 | 15/12/2022 |       15/02/2023     | 60 days  |      Implement automatic summarization of research trends in the searched literature                                                                                                    |
| Task #3 | 15/02/2022 |     15/03/2022       | 30 days  |     visualization of the tool (web app)                                                                                                     |
| Task #4        | 01/03/2022 |    01/05/2022        | 60 days  |  write report and presentation                                                                                                        |


## Correlation between the theoretical course and practical project
The accompanying theory courses *Machine Learning and Optimization* or *Machine Learning for Communication* teach basic and advanced machine learning (ML) and deep learning (DL) knowledge.


The core part of the project, in my opinion, is the automatic summarization of research trends/directions of the papers, which can be modeled as a **Topic Modeling** task in Natural Language Processing (NLP). This task requires machine learning and deep learning knowledge, such as word embeddings, transformers architecture, etc.

Therefore, I would like to take the Machine Learning and Optimization course or Machine learning for Communication course from EI department. And I think these theory courses should be necessary for a good ML/DL basis.