From f69802a584fbd5e54c29f210e4f1c6275e2a11fe Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jan=20Koco=C5=84?= <jan.kocon@pwr.edu.pl>
Date: Fri, 19 Feb 2021 14:59:19 +0000
Subject: [PATCH] Update README.md
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# Mapping WordNet onto Human Brain Connectome in emotion processing and semantic similarity recognition
+```
+@article{KOCON2021102530,
+ title = {Mapping WordNet onto human brain connectome in emotion processing
+ and semantic similarity recognition},
+ journal = {Information Processing & Management},
+ volume = {58},
+ number = {3},
+ pages = {102530},
+ year = {2021},
+ issn = {0306-4573},
+ doi = {https://doi.org/10.1016/j.ipm.2021.102530},
+ url = {https://www.sciencedirect.com/science/article/pii/S0306457321000388},
+ author = {Jan Kocoń and Marek Maziarz},
+ keywords = {Human brain connectome, WordNet, Desikan’s regions, Emotion lexicon,
+ Emotion processing, Semantic similarity},
+ abstract = {In this article we extend a WordNet structure with relations
+ linking synsets to Desikan’s brain regions. Based on lexicographer files
+ and WordNet Domains the mapping goes from synset semantic categories to
+ behavioural and cognitive functions and then directly to brain lobes. A
+ human brain connectome (HBC) adjacency matrix was utilised to capture
+ transition probabilities between brain regions. We evaluated the new
+ structure in several tasks related to semantic similarity and emotion
+ processing using brain-expanded Princeton WordNet (207k LUs) and Polish
+ WordNet (285k LUs, 30k annotated with valence, arousal and 8 basic
+ emotions). A novel HBC vector representation turned out to be
+ significantly better than proposed baselines.}
+}
+```
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