DellNLP solution facilitates the extraction of insights from text by proposing a central scalable API, including a novel automated query correction system that addresses various text pre-processing challenges and requirements. The main benefit DellNLP provides is incorporating Dell context which is missing from industry solutions and usually trained on open text corpora such as Wikipedia.

A novel automated query correction algorithm created for the project primarily performs detection and automated correction of spelling errors while minimizing false positives.

The solution was benchmarked with other widely available solutions including NLTK and spaCy.

In comparison, DellNLP provides:

• Accuracy gains of more than 10% over NLTK and spaCy, reducing spelling errors from 15% to 2%
• Major performance gains with a processing time of 1-2 minutes compared to 3-4 hours 

DellNLP can be immensely useful for current text processing applications as well as future applications, such as chatbots. Further, the algorithm and resource derivation process can be generalized. The same algorithm has the potential to process similar text found in other industry or academia contexts outside of Dell Technologies. The following figure compares the old and new processes.

Figure 3.            DellNLP as a central text pre-processing engine