From a future perspective and with the current advancements in technology, deep
reinforcement learning (DRL) is set to play an important role in several areas like …

Natural language processing (NLP) is crucial in the current processing of data because it
takes into account many sources, formats, and purposes of data as well as information from …

The efficiency of information retrieval systems primarily depends on the effective
representation of documents during query processing. This representation is mainly …

This article reviews and discusses feature extraction techniques used for text classification
as well as natural language processing in biomedical applications. This researchaims to …

Abstract Named Entity Recognition (NER) is a well-known problem for the natural language
processing (NLP) community. It is a key component of different NLP applications, including …

Social media platforms are an integral part of the lives of many people and are used as a
means of interaction, participation, and exchange of opinions, as well as used to change …

this paper proposes novel deep-learning models that can generate Muslim names. A
recurrent neural network (RNN) approach is used as the machine learning model. Generate …

Named Entity Recognition (NER) is important in many domains, such as information retrieval
and text classification. Typically, NER uses machine learning (ML) or rule-based methods to …

This paper presents NER-UK 2.0, a corpus of texts in the Ukrainian language manually
annotated for the named entity recognition task. The corpus contains 560 texts of multiple …

Indian court legal texts and processes are essential towards the integrity of the judicial
system and towards maintaining the social and political order of the nation. Due to the …