GRAB Thought Dataset for Consciousness Models
Study of mind and nature of intelligence is widely studied in cognitive science. Also, Artificial Wisdom which redefines the Artificial Wisdom is emerging research area where machine intelligence must collaborates with the constructive behavior and values of humanity. Thinking ability of human beings is recognized as the consciousness. Researchers from different domains like Cognitive Science, Artificial Intelligence, Psychology, Computer Engineering etc. are used to perform experimentations on consciousness or arousal of thoughts. As like as every research, research on consciousness or thought generation requires benchmark dataset using which well-build models can be realized. Since research on consciousness is emerging area for the researchers, benchmark dataset is not available or they are not getting benchmark dataset for their work. Unfortunately, research fraternity is striving hard in this regard. Some researchers are collecting data personally based on the application and performed their research work. But they can’t compare their work due to lack of using standard datasets. By considering this thrust in experimenting and developing computational models for consciousness or thoughts, GRAB Thought Dataset is prepared. The word GRAB is named to the dataset since initially it was created for and applied on Gharde-Ramteke Abhidhamma Based (GRAB) Thought computational model of consciousness.
GRAB Thought Dataset consists of 445 samples collected from various respondents by asking three questions by showing the images of different feelings, the images of basic shapes like mango, bitter guard, car, etc., the images of few popular personalities, and popular places. It is prepared in CSV format which can be accessible by any supporting applications like Microsoft Excel, etc. GRAB Thought dataset is suitable for the supervised and unsupervised machine learning techniques like Convolutional Neural Network, K-Nearest Neighbour technique, Support Vector Machines, etc. Primary objective of this database is to apply it for generating consciousness and identifying the different types of thoughts and classifying the mental states. Thoughts are classified into four major classes Wholesome (Good), Unwholesome (Bad), Resultant and Functional and mental states are classified into three classes Ethically Variable Factor, Unwholesome Factor and Beautiful Factor. Uses of these classes are completely optional for the user they can omit fields which are specifying these classes. Principle concern of this dataset is to capture the behavior and interest of the respondents and identify their personality traits or behavioral properties or thoughts or consciousness. This database is standardized by applying data cleaning and maintaining proper variance. Various operations of Natural Language Processing can be performed on this dataset.
GRAB Thought Dataset for consciousness models
Accessing CSV file consists of three steps.
Step 1. Open file in Microsoft excel. (Install any recent version of Microsoft Office, if it is not available)
Step 2. Check the all the fields. There are Image ID, Subject ID, Subject Age, Subject Answers, Thought Class, Thought Category, Mental Class and Mental category fields.
Step 3. Subject Answers at column E are useful for making any kind of operations on the dataset. Fetch the field for specific operations in your source code.
Step 4: If researcher wish to use the dataset for checking quality of thoughts then Thought Class at Column F and Thought Category at column G need to be fetched along with the subject answer at column E in the source code.
Step 5: If researcher wish to use the dataset for classifying mental state or mental factor then Mental Class at Column H and Mental Category at column I need to be fetched along with the subject answer at column E in the source code.