Aleksandr Sergeev
Capstone Poster – An Application of Semantic Relation Extraction Models
https://portfolios.cs.earlham.edu/wp-content/uploads/2020/05/488-Poster-v2.pdf
Capstone Paper – An Application of Semantic Relation Extraction Models
https://portfolios.cs.earlham.edu/wp-content/uploads/2020/05/Project_Paper__Final.pdf
CS488 – Week 15
This week I prepared my poster for the final submission, while editing also reworking my paper for the final submission next week. Last week I received feedback regarding user interaction and did research this week into what is the best way to build a GUI for my software.
CS488 – Week 14
This week I submitted my second draft of the paper, which required lots of results production as well as time to write. I graphed prediction trends between different materials of foreign data with my model which also was demonstrating how my model was performing. I received great feedback from my advisor regarding the poster and … Read more
CS488 – Week 13
This week we had the first draft of the poster due, which meant producing and visualizing a lot of results from my project. From this motivation, I compared my predictions across very different data (news articles, fictional novels, ect) and also was able to produce a convolution matrix that showed just how accurate my model … Read more
CS488 – Week 12
This week I further improved the pre-processing of sentences so that they are cleaner and easier to read on output. I then downloaded some previous year project posters to help with designing my own and have already completed half of it. It showed me that now I need to work further on results to present, … Read more
CS488 – Week 11
During the past couple of weeks, I made some good progress on my project. I now have a functioning driver file that the user will run to train or validate a model, or to predict from their input data. This has allowed me to tie up different parts of my software into one functioning project. … Read more
CS488 – Software Architecture Diagram
Please click on the title above to view my flow diagram.
CS488 – Week 8
This week I focused more on refining my idea and how it would flow for a user, which then helped me to create a flow diagram for this week. During this process, I realized some flows in my code were inefficient, so I changed the flow of information through certain functions to match up with … Read more
CS488 – Week 7
This week I began creating a model using the Keras Python library. I have been training it on the SemVal Task 8 2010 dataset, with accuracies of around 90% during training and 5 epochs and 60-65% validation accuracy. I was successfully able to save and reload the model. I will be working on increasing the … Read more
CS488 – Elevator Pitch
My project aims to see how applicable semantic relation extraction models are outside of their dataset. Semantic relations are how we draw knowledge and facts from a text and no text is the same and when we research we usually look for these relationships regarding certain subjects in the text important to us. I want … Read more
CS488 – Week 6
This week I was trying to run two different TensorFlow models with checkpoints, however, I could get the checkpoints to work which is key to my project. After a discussion with Dave, I have decided to implement a simple model myself using the Keras library since it is more abstracted and well documented, so it … Read more
CS488 – Week 5
This week I first worked on creating an outline for my final paper, which was useful as it sharpened my current understanding of my project and where it is headed. I also was working with a new model and was able to successfully train it, save checkpoints and load them. I also created basic pre-processing … Read more
CS488 – Week 4
This week I made efforts to get predictions from my model that was trained last week. However, after some hours spent understanding the code, I realized that this model is not for practical use but rather theoretical predictions, as each query set requires a supporting set. Following this setback, I have now found some models … Read more
CS488 – Week 3
This week I was able to create a saved checkpoint of my learning model for semantic relation extraction. This hopefully means I won’t need to train it further and can now focus on feeding it my data, which now needs to be pre-processed before being fed into the model. A basic GUI window was also … Read more
CS488 – Week 2
I forked MLMAN, a PyTorch model that achieved the second-highest accuracy of validation on the FewRel dataset for semantic relation extraction. Running locally with a useful amount of iterations, it took to long to train, so I will be training the module on hopper and saving the model there to fetch for local use. With … Read more
CS488 – Week 1 Update
This week I created the presentation for Wednesday, which helped to make clear to me my new current goal after work done over break. I have found some new datasets and repositories for models online, which I will be presenting to my advisor to figure out which best suits my project. I have also tried … Read more
CS388 – Week 7 – Update
I did not add an update to week 6 due to the long weekend but had been working on my literature review, which I finished today. It was very useful to read and re-read certain articles and realise some are useful and some are not. I now have further inspiration with where I can take … Read more
CS388 – Week 5 – Update
This week I researched deeper into my three ideas, and now have developed preferences and better understandings of them. Specifically, I believe the natural language processing idea where I will create summaries of subjects in PDF’s seems to not only be the most interesting to me, but the most achievable and most understandable of the … Read more
CS388 – Week 4 – Update
For this week, I started reading more into the papers that I found initially interesting for my ideas. I found some to be less relevant than others, but still drew some nice views that may be helpful later to shape my ideas. I want to perhaps find some replacement papers, and also talk to a … Read more
CS388 – Week 3 – Update
Idea: Breakdown of Mathematical Proofs Using Natural Language Processing I wish to use natural language processing to break down a bachelor-level mathematical proof into the components that make up a proof (e.g. given knowledge, statements, calculations). This will be shown in a GUI so that the user can clearly see the build-up of their proof. … Read more
CS 388 – Week 2 – Three Ideas
Breakdown of Mathematical Proofs Using Natural Language Processing I wish to use natural language processing to break down a bachelor-level mathematical proof into the components that make up a proof (e.g. given knowledge, statements, calculations). This will be shown in a GUI so that the user can clearly see the build-up of their proof. Without … Read more
CS388 – Week 1 – First Idea
Name of Your Project Breakdown of Mathematical Proofs Using Natural Language Processing What research topic/question your project is going to address? How available and useful current technology is to address completeness of mathematical proofs in intro/bachelor level mathematics courses. What technology will be used in your project? Python Natural Language Processing libraries, and SwiftUI for … Read more