Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Srividya K. Bansal"'
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
Autor:
Jaydeep Chakraborty, Siddharth Uppal, Ria Mehta, Srividya K. Bansal, Anurag Mishra, Akshay Kumar Dileep
Publikováno v:
ICSC
In recent years, template-based question answer has picked up steam as a solution for evaluating RDF triples. Once we delve into the domain of template-based question answering, two important questions arise which are, the size of the dataset used as
Publikováno v:
ICSC
For now, most search engines have limitations on finding the most suitable results from documents at a semantic level. This paper aims to provide users with more accurate document search results not only at a syntactic level but also on a semantic le
Autor:
Srividya K. Bansal, Mahmudul Hassan
Publikováno v:
SMDS
The proliferation of the semantic web in the form of Resource Description Framework (RDF) demands an efficient, scalable, and distributed storage along with a highly available and fault-tolerant parallel processing strategy. More precisely, the rapid
Publikováno v:
SBD@SIGMOD
Massive amounts of data, both structured and unstructured, are available to be harvested for competitive business advantage, sound government policies, and new insights in a broad array of applications. This paper specifically focuses on extraction,
Publikováno v:
ICSC
We propose a neural network-based approach to automatically learn and classify natural language questions into its corresponding template using recursive neural networks. An obvious advantage of using neural networks is the elimination of the need fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9563fa565cbc11269202566c5814f56
http://arxiv.org/abs/2004.13843
http://arxiv.org/abs/2004.13843
Publikováno v:
ICSC
With the dawn of Wikis, the collaboration of endless users and the rise of automated agents scraping thorough the internet in search of actionable information, it has become a necessity to create a framework that could serve as a translator between t
Publikováno v:
FIE
(Innovative Practice, Work in Progress.) Step-based tutoring systems, in which each step of a student’s work is accepted by a computer using special interfaces and provided immediate feedback, are known to be more effective in promoting learning th
Publikováno v:
2019 IEEE 13th International Conference on Semantic Computing (ICSC).
Autor:
Srividya K. Bansal, Mahmudul Hassan
Publikováno v:
ICSC
The rapid growth of semantic data in the form of Resource Description Framework (RDF) triples demands an efficient, scalable, and distributed storage and parallel processing strategies along with high availability and fault tolerance for its manageme