Search Results for author:
Found 3 papers, 1 papers with code
Distantly Supervised Question Parsing
The emergence of structured databases for Question Answering (QA) systems has led to developing methods, in which the problem of learning the correct answer efficiently is based on a linking task between the constituents of the question and the corresponding entries in the database.
ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies
The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing and interchanging information on machine learning algorithms, datasets, and experiments.
IQA: Interactive Query Construction in Semantic Question Answering Systems
Semantic Question Answering (SQA) systems automatically interpret user questions expressed in a natural language in terms of semantic queries.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
