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Found 6 papers, 2 papers with code
A survey on Big Data and Machine Learning for Chemistry
Herein we review aspects of leading-edge research and innovation in chemistry which exploits big data and machine learning (ML), two computer science fields that combine to yield machine intelligence.
On the role of words in the network structure of texts: application to authorship attribution
Well-established automatic analyses of texts mainly consider frequencies of linguistic units, e. g. letters, words and bigrams, while methods based on co-occurrence networks consider the structure of texts regardless of the nodes label (i. e. the words semantics).
Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts
The approach using linguistic features yielded higher accuracy if the transcriptions of the Cinderella dataset were manually revised.
Text authorship identified using the dynamics of word co-occurrence networks
The identification of authorship in disputed documents still requires human expertise, which is now unfeasible for many tasks owing to the large volumes of text and authors in practical applications.
Musical elements in the discrete-time representation of sound
In this article, each musical element is related by equations and algorithms to the discrete-time samples of sounds, and each of these relations are implemented in scripts within a software toolbox, referred to as MASS (Music and Audio in Sample Sequences).
Sound Popular Physics
Temporal stability in human interaction networks
The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered.
Social and Information Networks Physics and Society I.5.3
