MOTIVATION Recognizing words that are key to a document is important for ranking relevant scientific documents. Traditionally, important words in a document are either nominated subjectively by authors and indexers or selected objectively by some statistical measures. As an alternative, we propose to use documents' words popularity in user queries to identify click-words, a set of prominent wor...

The human disease search engine based on the query about factors (symptom, cause, position happening symptoms, i.e.,) helps users to conveniently diagnose they may have anytime, anywhere. Therefore, results returned by need be accurate and ranked reasonably so that can know which has highest probability for their query. We propose a method arrange diseases latent semantic analysis (LSA) techniq...

Imbalanced dataset merupakan hal yang sering ditemukan secara alami dalam proses penambangan data. Kondisi ini sangat mempengaruhi keakuratan klasifikasi data seperti terjadi komentar program Kampus Merdeka peneliti lakukan. Penelitian akan fokus pada penanganan untuk meningkatkan kinerja berasal dari aplikasi Twitter. Data diklasifikasikan ke empat kelas yaitu 0 (untuk informasi), 1 opini), 2 ...

Traditional text classification methods utilize term frequency (tf) and inverse document frequency (idf) as the main method for information retrieval. Term weighting has been applied to achieve high performance in text classification. Although TFIDF is a popular method, it is not using class information. This paper provides an improved approach for supervised weighting in the TFIDF model. The t...

Coverless information hiding has become a hot topic in recent years. The existing steganalysis tools are invalidated due to coverless steganography without any modification the carrier. However, for text relatively low capacity, this paper proposed big data method based on LDA (latent Dirichlet allocation) distribution and keyword TF-IDF (term frequency-inverse document frequency). Firstly, sen...

Text keywords have huge variance and to bridge the gap between country business segment which provides negligible information that a longtail it is imperative for us categorize queries provide middle ground also serve few other purposes. The paper will present those in-depth. Query categorization falls into of 'Multi-Class Classification' in domain natural language processing (NLP). However, re...

Ransomware attacks against Industrial Internet of Things (IIoT) have catastrophic consequences not only to the targeted infrastructure, but also services provided public. By encrypting operational data, ransomware can disrupt normal operations, which represents a serious problem for industrial systems. employs several avoidance techniques, such as packing, obfuscation, noise insertion, irreleva...

Abstractive summarization is the process of creating a condensed version of the given text document by collating only the important information in it. It also involves structuring the information into sentences that are simple and easy to understand. This paper presents the process that generates an abstractive summary by focusing on a unified model with attribute based Information Extraction (...

Hate speech on social media may spread quickly through online users and subsequently, even escalate into local vile violence heinous crimes. This paper proposes a hate detection model by means of machine learning text mining feature extraction techniques. In this study, the authors collected English-Odia code mixed data from Facebook public page manually organized them three classes. order to b...