The author has developed a tool that uses embeddings to rank word relationships quantitatively through word addition and subtraction, focusing on nouns and some proper nouns, allowing others to experiment with its results.
Python, TensorFlow for machine learning, and web technologies (HTML, CSS, JavaScript)
2025-05-15
- website
Highlight 1
The app effectively demonstrates complex concepts in natural language processing by visualizing word relationships using embeddings.
Highlight 2
The ranking mechanism based on distance and cosine symmetry greatly enhances the user experience by providing nuanced results rather than just the first match.
Highlight 3
The focus on common interpretations of homographs helps minimize ambiguity, making the app more user-friendly.
Improvement 1
The dataset currently contains only nouns and some proper nouns; expanding this to include verbs and adjectives could broaden the app's utility.
Improvement 2
The interface could benefit from additional tutorials or guidance for new users to help them understand how to maximize the tool's capabilities.
Improvement 3
Implementing user feedback mechanisms would allow for continuous improvement of the dataset and the application.
Product Functionality
Consider adding a feature that allows users to visualize the embeddings in a more dynamic way, such as through graphs or charts.
UI & UX
Enhance the user interface by adding tooltips and an onboarding tutorial for new users to improve accessibility.
SEO or Marketing
Implement a content marketing strategy that includes blog posts or video tutorials on the applications of word embeddings to drive traffic to the site.
MultiLanguage Support
Adding multi-language support would make the app more accessible to a broader audience, allowing users around the world to benefit from its functionality.
- 1
What types of words can I input into the app?
Currently, the app supports nouns and some proper nouns only.
- 2
How does the app rank the word associations?
The app uses a combination of distance and cosine symmetry to rank word relationships, providing a more nuanced set of results.
- 3
Is the application case sensitive?
Yes, the application is case sensitive, which means that word inputs must be entered with the correct case for accurate results.