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Here are some of the most interesting projects we have been involved in so far.

Computing Keyword Similarity

The goal of computing similarity is often to identify words or phrases that are related in meaning, and can be useful in a wide range of natural language processing tasks such as information retrieval, text classification, and machine translation. For instance, one use case that our team developed was create an NLP based algorithm to group phrases by the location specified.

Predicting Search Volume of Different Products sold online using their Rank

The idea behind this approach is that products with higher search volumes are likely to have higher sales and better rankings. By analyzing historical data on search volumes and product rankings, machine learning algorithms can identify patterns and make predictions about the relative rankings of different products based on their search volumes.

This kind of analysis can be useful for online sellers who want to optimize their product listings and improve their sales performance. By identifying the search terms and keywords that are most commonly associated with high-performing products, sellers can improve their product descriptions, titles, and other metadata to improve their search rankings and attract more customers.