Intent recognition

Our NLP engine and ML technology are used to recognize the intent of every user query. Each user query is first assessed by our engine; depending on what intent is recognized, the chatbot behaves accordingly. There are few basic intents that our chatbot can recognize:

1. Commands - can be used in the flow and allow the user to access certain features. Here are standard commands chatbots can handle:

   1. Main Menu - shows the main menu with the buttons (examples of messages that will trigger it: “Menu“, “Get main menu“ and similar).

   2. Restart - triggers a welcome message and restarts the chatbot (examples: “Start“, “I want to restart“).

   3. Question - triggers FAQ flow and allows the user to ask questions (examples: “I have a question“, “Can I ask you something?“ etc.).

   4. Feedback - if the feature is enabled, allows the user to access feedback functionality (examples: “I want to give feedback“ or “Can I write feedback?“).

   5. Help - allows user to access your help message - usually with main menu buttons (examples: “I need help!“, “Help me!“ etc.)

   6. Subscriptions - option for the user to see their job updates subscriptions and control them (examples: “Show me my subscriptions“, “Job alerts“, “Receive job updates“).

2. Small talks like “Hello“ or “How are you” that trigger chatbot-specific small talk response.

3. Find Job requests that allow the user to trigger job discovery flow or lead them straight to the job carousel.

4. Other - questions that should end up in your Training view and get a response from your FAQ Dataset.

You can see an overview of that process here:

Open

Synonyms

In the case of Find Job intent, we recognize two basic entities: Profession (job category or type) and Location (can be city or country). In both cases we are able to create global synonyms, which will impact all chatbots using that certain language. Those synonyms will allow your users to look through your jobfeed using names of locations and professions that maybe not correspond exactly to the way you have phrased them on your side.

Example: In your jobfeed you have New York City as location. But your users may not use the word “New York City“ while looking for the job positions in that city. “Work in New York“, “I am looking for a Marketing position in NYC“ or “Do you have open positions in NY?“ all are valid search requests, and global synonyms can make sure that New York City is understood when New York, NYC, or NY are given.