In this article, we shall discuss how to apply Artificial Intelligence (AI) in chat filters.
If you are building a chat room, you need to create a chat filter to remove offensive words from the conversation. A chat filter is a script commonly used in chat rooms for automatically scanning the users’ comments. This process starts immediately after posting the comments, and filters remove or censor inappropriate words. These filters also decide the flow of the chat in a conversation.
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As technology is advancing with time, the application of AI is increasing in every domain. Human beings capabilities like understanding the complexities of various languages, computer vision, speech, and building new intelligent ideas are now possible using AI technology. For that, we have to update with the latest developments in AI and its advanced areas.
Here, we will discuss the application of Artificial Intelligence in chatbot filters.
There are two categories of chat filters used in chat rooms or internet forums – the basic and advanced chatbot filters. The basic bot filters scan only for particular strings of letters and censor them. It doesn’t take care of the meaning of those letters in the context of the sentence.
Advanced chatbot filters examine the letters or words in the sentence context, and hence, their filtering is more sophisticated. Some more advanced chatting filters use a regular expression to find and replace terms in a sentence.
1. Types of Chat Filters
There are five different types of chatbot filter:
Attribute: In this type of filter, you have to create your quality to create a rule.
Lifespan: In this type, the bot acts based on the lifespan value.
Score: Here, we use the confidence score value to choose the response that should allow the bot trigger.
Resolve Query: In this filter, the bot responds depending on the user’s input.
Trigger: Determine trigger to activate bot responses and actions.
These are the different filters that may apply to a chatbot. We can use multiple filters for a single response. A user can see the reactions only if they meet the criteria in the filter.
2. Need for Artificial Intelligence in Chat Filters
Artificial Intelligence changed the way we think about data. It changed the people’s paradigm about how we integrate information and analyze data, and based upon the data, how to improve the decision-making ability of machines. AI is already interfering with our day-to-day life. From Google search results recommendations to Apple’s virtual assistant Siri, we use AI in every aspect of life.
Typically most filters use a binary allow/disallow list, but we know that languages are not binary. They are complex and modulated.
In many older internet forums, some common swear words will be allowed based on context. One can build a regular expression or RegEx tool, and it can filter the string out of terms, but it cannot distinguish between some critical phrases. For that, we need to apply artificial intelligence and natural language processing in creating chat rooms.
3. Application of Natural Language Processing in Chat Filters
In the case of chatbot filters, we use natural language processing. NLP is a sub-domain of AI that deals with the interaction between computers and human language. It helps the filters process and analyses the vast amount of natural language data that results in a machine capable of understanding the available content more clearly.
One can program our chatbots to reply according to the context of the conversation and the data about the user. For example, one may ask the visitor whether he/she is a vegetarian or non-vegetarian and display the menu based upon the visitor’s reply using chat filters.
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In another example, consider a situation where you want your bot to forward registered users to your website and the new visitors to a registration form. Then, we have to create a flow to check if the user is registered or not.
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If a user clicks on yes, it shows him one kind of bot response and if he chooses no, it would lead to a different action. We can implement all this filtering in a chatbot by using NLP.
It is not easy for computers to understand the rules that dictate information passing using natural language processing. Sometimes these rules may be highly complex; for example, when we use a sarcastic remark to convey the message. On the other hand, sometimes there may be situations where these rules may be low-levelled; for example, one can use the character “s” for the plural form of the word.
To comprehensively understand the human language, one needs to know the language and how the terms are connected to the sentence to deliver the desired message.
NLP necessitates the algorithms to identify and extract the natural language rules for converting unstructured language data into structured language data. This is how AI and NLP are applied to chat filters.
Overall, we can say that artificial intelligence can make chatbot filters very easy and efficient. However, the techniques deployed in a particular scenario would vary case by case.
4. Frequently Asked Questions (FAQs)
a. What are the chatbots and chat filters?
Ans: Chatbots are software application for conducting an online conversation between humans and machines. It can be a text-based or text-to-speech-based system and can respond according to the user’s query.
A chat filter is used in a chatbot to censor the inappropriate words or sentences in a chat. Chat filters decide the flow of the conversation based on the user’s input.
b. What are Artificial Intelligence (AI) and Natural Language Processing (NLP)?
Ans: It can learn a specific task by a machine without explicitly programming for that task. AI systems are designed to make decisions by analyzing real-time data.
NLP is a subdomain of AI, specially programmed for interaction between humans and computers. Using NLP, a machine can read, decipher, understand, and make sense of a human language in such a practical manner.
c. How to apply AI into a chat filter?
Ans: Using a particular NLP algorithm, we can apply artificial intelligence into chat filters to smooth the undesirable content in a chat. There are different ways in which we can control the flow of the conversation in a chat room.