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NLP Topic Clustering

An NLP Topic Cluster, where all these specific terms are extracted from the body of relevant text, and then a cluster of the relationships between each term is set.

Challenge

Online merchandising and smart chatbots rely on understanding a group of terms specific to a given vertical industry. For example, retail clothing would have terms about ‘color’ and ‘size.’ The first step in creating an excellent AI-driven experience is building a “Natural Language Processing (NLP) Topic Cluster”, where all specific terms are extracted from the body of relevant text. Then, a cluster of the relationships between each term is set.

Interplay creates Natural Language Processing (NLP) topic classification models.

Solution

With Interplay®, enterprises no longer have to worry about analyzing vast amounts of data and finding similarities within the datasets. Interplay can be used to create an NLP topic classification model, which recognizes patterns amongst textual data and classifies them.

NLP topic clustering is a significant engine for many AI applications. Using this technology, enterprises can develop informed business strategies by quickly analyzing customer feedback grouped into trends, creating chatbots that can respond to various customer terminologies, and efficiently conducting accurate competitive analyses.

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