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Semantic Cells: Evolutional Process to Acquire Sense Diversity of Items
Previous models for learning the semantic vectors of items and their groups, such as words, sentences, nodes, and graphs, using distributed representation have been based on the assumption that the basic sense of an item corresponds to one vector composed of dimensions corresponding to hidden contexts in the target real world, from which multiple senses of the item are obtained by conforming to lexical databases or adapting to the context.
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Well-being
Feature concepts and data leaves have been invented using datasets to foster creative thoughts for creating well-being in daily life.
Generating a Map of Well-being Regions using Multiscale Moving Direction Entropy on Mobile Sensors
The well-being of individuals in a crowd is interpreted as a product of the crossover of individuals from heterogeneous communities, which may occur via interactions with other crowds.
Data Leaves: Scenario-oriented Metadata for Data Federative Innovation
A method for representing the digest information of each dataset is proposed, oriented to the aid of innovative thoughts and the communication of data users who attempt to create valuable products, services, and business models using or combining datasets.
