5 citations · 7 across the 4 of their papers we have counts for
6 papers
Knowledge-driven Natural Language Understanding of English Text and its Applications
Kinjal Basu, Sarat Varanasi, Farhad Shakerin +2
Understanding the meaning of a text is a fundamental challenge of natural language understanding (NLU) research. An ideal NLU system should process a language in a way that is not…
SQuARE: Semantics-based Question Answering and Reasoning Engine
Kinjal Basu, Sarat Chandra Varanasi, Farhad Shakerin +1
Understanding the meaning of a text is a fundamental challenge of natural language understanding (NLU) and from its early days, it has received significant attention through questi…
White-box Induction From SVM Models: Explainable AI with Logic Programming
Farhad Shakerin, Gopal Gupta
We focus on the problem of inducing logic programs that explain models learned by the support vector machine (SVM) algorithm. The top-down sequential covering inductive logic progr…
Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models
Farhad Shakerin
We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models. We reduce the problem of search for best clauses to instances of t…
Induction of Non-Monotonic Rules From Statistical Learning Models Using High-Utility Itemset Mining
Farhad Shakerin, Gopal Gupta
We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models. We reduce the problem of search for best clauses to instances of t…
A New Algorithm to Automate Inductive Learning of Default Theories
Farhad Shakerin, Elmer Salazar, Gopal Gupta
In inductive learning of a broad concept, an algorithm should be able to distinguish concept examples from exceptions and noisy data. An approach through recursively finding patter…