In this work we evaluate domain-specific embedding models induced from textual resources
in the Oil and Gas domain. We conduct intrinsic and extrinsic evaluations of both general …

The multi-label customer reviews classification task aims to identify the different thoughts of
customers about the product they are purchasing. Due to the impact of the COVID-19 …

In order to accelerate the performance of various Natural Language Processing tasks for
Roman Urdu, this article for the very first time provides 3 neural word embeddings prepared …

Membrane transport proteins and their substrate specificities play crucial roles in various
cellular functions. Identifying the substrate specificities of membrane transport proteins is …

Automatic synonym extraction plays an important role in many natural language processing
systems, such as those involving information retrieval and question answering. Recently …

This paper presents a summary of research findings for a new reacitve phishing
investigative technique using Web bugs and honeytokens. Phishing has become a rampant …

Automatic synonym recognition is of great importance for entity-centric text mining and
interpretation. Due to the high language use variability in real-life, manual construction of …

Extracting synonyms from textual corpora using computational techniques is an interesting
research problem in the Natural Language Processing (NLP) domain. Neural techniques …

Objectives An important component of processing medical texts is the identification of
synonymous words or phrases. Synonyms can inform learned representations of patients or …

This paper considers the question: In what ways can artificial intelligence assist with
interdisciplinary research for addressing complex societal problems and advancing the …