1887
Mental Model Ascription by Intelligent Agents
  • ISSN 1572-0373
  • E-ISSN: 1572-0381
USD
Buy:$35.00 + Taxes

Abstract

Humans routinely transmit and interpret subtle information about their mental states through the language they use, even when only the language text is available. This suggests humans can utilize the linguistic signature of a mental state (its mindprint), comprised of features in the text. Once the relevant features are identified, mindprints can be used to automatically identify mental states communicated via language. We focus on the mindprints of eight mental states resulting from intentions, attitudes, and emotions, and present a mindprint-based machine learning technique to automatically identify these mental states in realistic language data. By using linguistic features that leverage available semantic, syntactic, and valence information, our approach achieves near-human performance on average and even exceeds human performance on occasion. Given this, we believe mindprints could be very valuable for intelligent systems interacting linguistically with humans. Keywords: mental state; linguistic features; mindprint; natural language processing; information extraction
Loading

Article metrics loading...

/content/journals/10.1075/is.15.3.01pea
2014-01-01
2019-10-17
Loading full text...

Full text loading...

References

http://instance.metastore.ingenta.com/content/journals/10.1075/is.15.3.01pea
Loading
  • Article Type: Research Article
Keyword(s): information ext , linguistic featuresmindprint , mental state and natural language processing

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error