Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels
Environmental factors determine the smells we perceive, but societal factors factors shape the importance, sentiment and biases we give to them. Descriptions of smells in text, or as we call them `smell experiences', offer a window into these factors, but they must first be identified. To the best of our knowledge, no tool exists to extract references to smell experiences from text. In this paper, we present two variations on a semi-supervised approach to identify smell experiences in English literature. The combined set of patterns from both implementations offer significantly better performance than a keyword-based baseline.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
FrameNet-like Annotation of Olfactory Information in Texts
Although olfactory references play a crucial role in our cultural memory, only few works in NLP have tried to capture them from a computational perspective. Currently, the main challenge is not much the development of te…
Natural Language UnderstandingA Multilingual Benchmark to Capture Olfactory Situations over Time
We present a benchmark in six European languages containing manually annotated information about olfactory situations and events following a FrameNet-like approach. The documents selection covers ten domains of interest …
ToolFactory: Automating Tool Generation by Leveraging LLM to Understand REST API Documentations
LLM-based tool agents offer natural language interfaces, enabling users to seamlessly interact with computing services. While REST APIs are valuable resources for building such agents, they must first be transformed into…
AI AgentAn Olfactory EEG Signal Classification Network Based on Frequency Band Feature Extraction
Classification of olfactory-induced electroencephalogram (EEG) signals has shown great potential in many fields. Since different frequency bands within the EEG signals contain different information, extracting specific f…
ClassificationEEGEEG Signal ClassificationElectroencephalogram (EEG)Human-Machine Cooperative Multimodal Learning Method for Cross-subject Olfactory Preference Recognition
Odor sensory evaluation has a broad application in food, clothing, cosmetics, and other fields. Traditional artificial sensory evaluation has poor repeatability, and the machine olfaction represented by the electronic no…
EEGElectroencephalogram (EEG)