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In this research paper we address the importance of Product Data Management (PDM) with respect to its contributions in industry. Moreover we also present some currently available major challenges to PDM communities and targeting some of these challenges we present an approach i.e. I-SOAS, and briefly discuss how this approach can be helpful in solving the PDM communitys faced problems. Furthermore, limiting the scope of this research to one challenge, we focus on the implementation of a semantic based search mechanism in PDM Systems. Going into the details, at first we describe the respective field i.e. Language Technology (LT), contributing towards natural language processing, to take advantage in implementing a search engine capable of understanding the semantic out of natural language based search queries. Then we discuss how can we practically take advantage of LT by implementing its concepts in the form of software application with the use of semantic web technology i.e. Ontology. Later, in the end of this research paper, we briefly present a prototype application developed with the use of concepts of LT towards semantic based search.
It is necessary to improve the concepts of the present web based graphical user interface for the development of more flexible and intelligent interface to provide ease and increase the level of comfort at user end like most of the desktop based appl
Adversarial training, a method for learning robust deep neural networks, constructs adversarial examples during training. However, recent methods for generating NLP adversarial examples involve combinatorial search and expensive sentence encoders for
The COVID-19 pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread. Many of these difficulties are fundamentally information needs
We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP publications. To identify the most important contribution sentences i
Performance prediction, the task of estimating a systems performance without performing experiments, allows us to reduce the experimental burden caused by the combinatorial explosion of different datasets, languages, tasks, and models. In this paper,