Visible to the public New TSBuilder: Shifting towards Cognition

TitleNew TSBuilder: Shifting towards Cognition
Publication TypeConference Paper
Year of Publication2019
AuthorsBakhtin, Vadim V., Isaeva, Ekaterina V.
Conference Name2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
Keywordsartificial thinking, Biological neural networks, Classification algorithms, Cognition, data mining, decision making, Deep Learning, Human Behavior, human thinking, learning (artificial intelligence), machine learning, multilayer Rosenblatt perceptron, natural language processing, natural language texts, Neural Network, Neurons, new TSBuilder, pubcrawl, Resiliency, rigid categorization, rigidity, Scalability, Standards, supervised machine learning, Task Analysis, term length, term system builder, term system building, term system construction, text analysis, text mining, TSBuilder, word terms identification
AbstractThe paper reviews a project on the automation of term system construction. TSBuilder (Term System Builder) was developed in 2014 as a multilayer Rosenblatt's perceptron for supervised machine learning, namely 1-3 word terms identification in natural language texts and their rigid categorization. The program is being modified to reduce the rigidity of categorization which will bring text mining more in line with human thinking.We are expanding the range of parameters (semantical, morphological, and syntactical) for categorization, removing the restriction of the term length of three words, using convolution on a continuous sequence of terms, and present the probabilities of a term falling into different categories. The neural network will not assign a single category to a term but give N answers (where N is the number of predefined classes), each of which O ∈ [0, 1] is the probability of the term to belong to a given class.
DOI10.1109/EIConRus.2019.8656917
Citation Keybakhtin_new_2019