Whether it's consumer reviews, support tickets, social media conversations or articles, data hides a story to reveal.
Uncover with Kimola's text analysis capabilities.Start Your Free Trial! No credit card · No commitment · Cancel any time
Turn your text data into a well-organized dataset by identifying entities in your dataset. See the list of entities that are mentioned on your dataset file in categories such as person names, organizations, interests, locations, artworks and many more.
Filter your dataset by the most popular entities and their categories. Access the relations within terms and see how they are mentioned in a text.
Kimola offers a solid technology that uses machine learning techniques to recognize named entities. Just upload your dataset file and get the list of popular entities and their categories.
Languages contain words with different meanings and they also evolve in a way that words keep gaining new meanings. This explains one of the major challenges in text analysis: Word-sense disambiguation.
The word “bass” has different meanings in “I like to hear the bass sound.” and “I like to eat grilled bass.” sentences. Even though it’s an easy process for humans to understand what “bass” refers to in these sentences, it's a technological challenge for algorithms to detect the right meaning with an acceptable accuracy.
Kimola has a unique technology that uses machine learning techniques to understand the meaning of a term or a single word. Just upload your dataset file and get the list of popular words or terms based on their meanings in the given context.
Automatically classify your data based on the context, whether it contains consumer reviews, news or articles.
Upload your training set and build a custom machine learning model based on your custom business needs.
Data analysis starts with data. Make use of Kimola's data scraping extension to access consumer reviews.
Since data analytics is a highly sophisticated area, besides offering a good UI/UX, Kimola provides educational content such as articles and video tutorials. Also, you will have live chat support in the dashboard.
Understanding and analyzing customer feedback will help you create a customer feedback loop.
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The classification process tags the entire text block with pre-defined labels in a machine learning model. On the other hand, analyzing process focuses on components of a text block, starting from words to terms. Also, named-entity recognition is subject to text analysis. So, analyzing and classifying a text block are entirely different processes.
No, Kimola provides all the technical infrastructure to analyze a dataset contextually, and all you need is to upload your data set.
No, Kimola uses a single technical infrastructure for every text analysis process. It's a solid and up-to-date artificial intelligence work with unique technology that only changes from language to language.
Yes, you don't need to create your custom machine learning model or event have to classify your datasets with pre-built models. You can only choose to analyze your text when you upload your data set.
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