Intent Classification to Classify User Inputs into Predefined Intents

Intent classification or intent recognition provides accurate descriptions of natural language speech based on a predefined set of intentions. With our high-quality chatbot intent classification datasets, it is possible to develop smart UIs and NLP models that are able to identify and categorize users' intents more accurately.

Contact Us Now
intent classification

Our Approach to Intent Classification Process

Intent Classification is a natural language processing (NLP) task used to determine the user’s intent in a sentence or phrase. Data labeling experts at Cogito labels the intent of a sentence or phrase as a particular class or category. It classifies user input into categories such as “greetings”, “questions”, and “requests”. Applications such as chatbots can use it to better understand user input and respond to their requests more accurately.

Our Intent Classification Services Involve:

Importing Datasets

Importing Datasets

We at Cogito are well aware of what it takes to source the quality datasets that can be used to train an intent classification model. Among the sources from which we obtain data for text intent classification are open source datasets, custom datasets, and conversational datasets.

We, however, focuse primarily on constructing custom datasets from analyzing conversations, customer service logs, surveys, and other sources.

Analyzing Datasets

As a next step, we analyze the imported datasets and determine the tags referring to different intentions. For developing chatbot intent classification datasets, we first identify the purpose or intent of the data by analyzing the data’s structure, content moderation and context.

Analyzing the structure, content, and context of the data allows classification of the data’s intent. This herlps with insight into customer preferences, market trends, etc.

Analyzing Datasets
Tagging Appropriate intent to the Text

Tagging Appropriate intent to the Text

Engage experts to add appropriate tags to the intent classification dataset that indicate the intent contained within them. NLP techniques are used to apply tags to texts to identify parts of speech, named entities, intents, and emotions.

NLP systems, such as intent classifiers, commonly use this process to improve their accuracy. Text tags can also be used to automate the analysis of text and to extract meaningful information from it.

Intent Classification Use Cases

Intent classification is commonly used in chatbots and virtual assistants to accurately understand and respond to user inputs. It is used to identify user intent from a given user utterance or phrase, and is used to determine the next best action for the system to take. It can also be used to categorize user feedback or to detect sentiment in customer reviews.

Identifying Customers’ Orientation

Identifying Customers’ Orientation

Intent Classification is often used in automated Q&A systems and chatbots. It enables organizations to focus more on their customers, especially in areas like sales. It can assist you in reacting to leads quicker, coping with high volumes of inquiries, and providing tailored service.

Analyzing Email intent

Analyzing Email intent

Depending on the intent contained in an email, intent classification can be useful for sorting and serving users. Determining the intent of emails can help businesses provide their prospects/potential or existing customers with what they need.

Chatbot intent Classification or Recognition

Chatbot intent Classification or Recognition

Chatbots use NLP to comprehend the user’s intent. Intent classification enables the chatbot to interpret the user’s message, while machine learning classification algorithms classify it based on the training data and give the appropriate answer.

Outsource To Us

Intent recognition datasets are an integral part of Cogito’s NLP and chatbot solutions. We gather, categorize, and analyze the datasets in a variety of ways to make them usable for the chatbot application to understand messages and respond wisely as per the intent

Quality on a Promise

Quality on a Promise

Our team is committed to delivering high-quality Text Annotations. Our training data is therefore tailored for the applications of our clients.

Uncompromised Data Security

Uncompromised Data Security

Data security and confidentiality are of utmost importance to us. At all points in the annotation process, our team ensures that no data breaches occur.

Scalable with Quick Turnaround Time

Scalable with Quick Turnaround Time

We at Cogito claim to have the necessary resources and infrastructure to provide Text Annotation services on any scale while promising quality and timeliness.

Flexible Pricing

Flexible Pricing

Besides offering flexible pricing, we can tailor our services to suit your budget and training data requirements with our pay-as-you-go pricing model.

Get Us On Board

Cogito can offer high levels of quality while providing intent classification services with the help of professionals skilled in intent tagging and text annotation. Bringing over 1500 data experts together at Cogito can help you develop successful NLP-based datasets for Chatbot Training.

Talk to our Solutions Expert

    * Mandatory fields

    We're committed to your privacy. Cogito uses the information you provide to us to contact you about our relevant content, products, and services. For more information, check out our Privacy Policy.