12 Best Text Classification Tools and Services
When it involves mining and analyzing text data, text classification plays a crucial role. Categorizing text supported sentiment, genre, status, or intent is beneficial for tasks like language detection, customer feedback analysis, and fraud detection. However, arriving at these data insights will be both time and labor-intensive when done manually. Fortunately, with the event of machine learning and language processing, much of the method can now be automated.
Below, we’ve compiled a listing of open source tools for developing your own text system. We’ve also listed available services and platforms that include text classification as a part of their suite of text analysis tools.
Open Source Tools
Apache OpenNLP: OpenNLP supports common NLP tasks like tokenization, sentence segmentation, named entity extraction, and language detection. It also offers text classification through its Document Classifier, which allows you to coach a model that categorizes text supported pre-defined categories.
The tongue Toolkit: Commonly spoken as NLTK, the language Toolkit is an open-source, community-driven project for linguistic communication processing tasks. The creators have written a guidebook that walks through the basics of writing Python programs for tasks including text classification, analyzing linguistic structure, and more.
Orange: Specializing in building data analysis workflows and visualizations, Orange offers a number of NLP and analytics tools. These include text classification, social media data analysis, and sentiment analysis. Their team also offers online training courses in data processing to assist people to understand data exploration without the coding and also the math.
TextFlows: This online platform is meant for the composition, execution, and sharing of text mining and NLP workflows for text analysis tasks. It uses visual programming to simplify complex procedures and is cloud-based, meaning you’ll be able to work anywhere without installing it on your local disk drive.
Testable: Built on top of the Orange framework, Testable is made specifically for analyzing and processing texts visually. By adding blocks to make processing “recipes”, you’ll create data analysis workflows and gain visual insights into them quickly.
DatumBox: The DatumBox API currently offers 14 different functions as a part of its machine learning platform, including topic classification, subjectivity analysis, keyword extraction, and more. It supports a range of various methods and algorithms that may be found on their official website.
Text Classification Services
MeaningCloud: MeaningCloud could be a set of APIs (application programming interfaces) for text analytics, including text classification. Its flexibility makes it an excellent option for developers, but the coding requirements make it a harder option for non-technical users. However, a free version is additionally available for processing up to twenty,000 requests per month if you’d wish to try it out.
MonkeyLearn: The MonkeyLearn platform may be wont to build a custom text classifier to categorize your text data as per your programmed specifications. the method involves uploading your data, defining your tags, and training the model by tagging data for it to find out from. you’ll be able to then test it, improve it as necessary, and put it to figure.
Google Cloud NLP: If your data is already stored on Google’s cloud, their NLP service could also be a simple thanks to smoothly transition into text analysis. The AutoML language platform allows you to upload documents supported specific keywords and phrases, then train a model and evaluate it.
IBM Watson: The Watson language Classifier is a component of a collection of text analysis tools available with IBM Watson. If you have got your training data ready, the classifier is simple to coach, and therefore the system is constructed to form it easy to integrate into applications. Do confine mind however that coding is also necessary to essentially get the foremost out of their classifier.
Aylien: Specializing within the analysis of reports articles, Aylien’s text analysis allows you to form a custom text classification model without leaving your browser. They boast a straightforward process that doesn’t require coding, and a database of documents from which to begin building a dataset.
Rosette: a part of Basis Technology, Rosette’s text system comes pre-trained on the IAB Tech Lab Content Taxonomy, but can even be customized through keyword-based training or a training dataset.
Text Classification Datasets
To make the foremost of the tools above, you’ll need a dataset of annotated text data to coach your model to accurately classify text per your specifications.
If you’re searching for text classification datasets to assist with the training of a customized machine learning model, we’ve compiled datasets from across the online. you’ll be able to find datasets for product reviews, online content evaluation, news classification, and available dataset repositories. they ought to provide a decent place to begin for machine learning projects.
The Lionbridge Text Classification Tool
There is a spread of approaches you’ll be able to desire data labeling, but if you’re unsure of where to begin, get involved to be told about our own text classification tools and services.
Lionbridge provides data services to gather, clean, and annotate text data for a good range of use-cases. you’ll found text classification projects on our dedicated data annotation platform together with your own internal team. Alternatively, you’ll work with our community of 1,000,000+ qualified annotators, data scientists, and project managers to assist complete your next big project.