Text-Intent Classification Task
(Redirected from Intention Classification Task)
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An Text-Intent Classification Task is a text-item classification task that maps a text item to a user intention category.
- Context:
- It can (typically) involve transforming Natural Language Input into discrete Intent Categories, such as "Message Send" or "Reminder Set."
- It can (often) be a component in Conversational AI Systems or Voice Assistants, enabling them to understand user commands.
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- It can range from being a Simple Text-Intent Classification Task to being a Complex Text-Intent Classification Task.
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- It can be solved by a Text-Intent Classification System (that implements a text-intent classification algorithm).
- It can include Ambiguous Intents.
- It can include Intent Disambiguation mechanisms for resolving conflicting user requests.
- ...
- Example(s):
- “tell Jane that I'll be late” ⇒
Message Send. - “send a message that I'll be late to Jane” ⇒
Message Send. - “remind me to buy groceries at 6 PM” ⇒
Set Reminder. - “what is the weather in Paris tomorrow?” ⇒
Weather Query. - ...
- “tell Jane that I'll be late” ⇒
- Counter-Example(s):
- Semantic Parsing, which focuses on extracting structured meaning representations from text.
- Named Entity Recognition, which identifies specific entities in the text without inferring user intent.
- Topic Classification, which categorizes text by general topics rather than specific user intentions.
- See: Text Understanding, Sentiment Detection, Query Intent, Conversational AI, Intent Detection Models.
References
2015
- (Ding et al., 2015) ⇒ Xiao Ding, Ting Liu, Junwen Duan, and Jian-Yun Nie. (2015). “Mining User Consumption Intention from Social Media Using Domain Adaptive Convolutional Neural Network.” In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. ISBN:0-262-51129-0
- QUOTE: ... Social media platforms are often used by people to express their needs and desires. Such data offer great opportunities to identify users' consumption intention from user-generated contents, so that better tailored products or services can be recommended. ...