Due to the lengthy and complex nature of legal documents, automatic summarization has
very high applicability in this domain. Recently, several researchers have proposed …

Abstractive dialogue summarization is a challenging task for several reasons. First, most of
the key information in a conversation is scattered across utterances through multi-party …

Recent years have witnessed the rapid adoption of mobile devices and significant growth in
the use of mobile apps. However, the large number of mobile apps makes it difficult for users …

Human health depends on choosing food ingredients that align with dietary needs and
avoid allergens. However, consumers often encounter unfamiliar ingredients that require …

In recent years, the fields of Natural Language Processing (NLP) and Generative Artificial
Intelligence (AI) have seen significant advancements, particularly in the domain of legal text …

The part of speech (PoS) tagging is a core component in many natural language processing
(NLP) applications. In fact, the PoS taggers contribute as a preprocessing step in various …

Sentence extraction in news document summarization determines representative sentences
primarily by employing the news feature known as news feature score (NeFS). NeFS can …

Topic Models are representations of the given text. Topic models are unsupervised in nature
because they totally depend on word distributions. Few generative topic models obtain the …

Memahami makna utama yang terkandung dalam beberapa dokumen tentu tidak mudah
dan membutuhkan waktu yang cukup lama. Menanggapi masalah tersebut, penelitian …

Abstract News Feature Scoring (NeFS) merupakan metode pembobotan kalimat yang sering
digunakan untuk melakukan pembobotan kalimat pada peringkasan dokumen berdasarkan …