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Register a new userUnderstanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence
فهم الفضاء الدلالي: كيف تعاني كلمة تتكيف ديناميكيا في سياق الجملة
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كيف يفهم الناس معنى كلمة صغيرة "عند استخدامها لوصف البعوض أو الكنيسة أو كوكب؟في حين أن البشر لديهم قدرة رائعة على تشكيل معاني من خلال الجمع بين المفاهيم القائمة، فإن نمذجة هذه العملية تحديا.تتناول هذه الورقة هذا التحدي من خلال Cerebra (تمثيلات المعنى المعنى المعني بالسياق في الدماغ) نموذج الشبكة العصبية.يميز Cerebra كيف يتكيف معاني الكلمات بشكل ديناميكي في سياق جملة من خلال الحكم المتحلل في جمهورية FMRI إلى الكلمات والكلمات في ميزات الدلالية المجدولة في الدماغ.يوضح أن الكلمات في سياقات مختلفة لها تمثيلات مختلفة والكلمة التي تعني التغييرات بطريقة ذات معنى إلى الموضوعات البشرية.يمكن أن تستخدم التمثيلات القائمة على سياق Cerebra لجعل تطبيقات NLP أكثر تشبه الإنسان.
How do people understand the meaning of the word small'' when used to describe a mosquito, a church, or a planet? While humans have a remarkable ability to form meanings by combining existing concepts, modeling this process is challenging. This paper addresses that challenge through CEREBRA (Context-dEpendent meaning REpresentations in the BRAin) neural network model. CEREBRA characterizes how word meanings dynamically adapt in the context of a sentence by decomposing sentence fMRI into words and words into embodied brain-based semantic features. It demonstrates that words in different contexts have different representations and the word meaning changes in a way that is meaningful to human subjects. CEREBRA's context-based representations can potentially be used to make NLP applications more human-like.
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