In traditional document clustering methods, a document is considered a bag of words. The fact that the words may be semantically relateda crucial information for clusteringis not taken into account. The feature vector representing the document is constructed from the frequency count of document terms. To improve results, weights calculated from techniques like Inverse Document Frequency (IDF) a...

On-line text documents rapidly increase in size with the growth of World Wide Web. To manage such a huge amount of texts,several text miningapplications came into existence. Those applications such as search engine, text categorization, summarization, and topic detection are based on feature extraction.It is extremely time consuming and difficult task to extract keyword or feature manually.So a...

Document classification nowadays is an easy thing to do because there are the latest methods get maximum results. using term weighting TF-IDF-ICF method has been widely studied. Documents used in this research generally use large documents. If TF-IDF a short text document such as Thesis Title, will not perfect score from Because IDF calculate weight of words that always appear be few, ICF often...

Emotions are expressions manifested by individuals in response to what they see or experience. In this study, emotions were examined through individuals' tweets regarding the election issues Indonesia 2024. The collected then labeled based on using emotion wheel, which consisted of six categories: joy, love, surprise, anger, fear, and sadness. After labeling process, next step involved weightin...

Natural language processing (NLP) task has achieved excellent performance in many fields, including semantic understanding, automatic summarization, image recognition and so on. However, most of the neural network models for NLP extract text a fine-grained way, which is not conducive to grasp meaning from global perspective. To alleviate problem, combination traditional statistical method deep ...

Elektronik posta, internet üzerinden gönderilen bir tür dijital mektuptur. postalar aracılığı ile belge, resim, video, müzik gibi her türlü dosya gönderilip alınabilmektedir. Düşük maliyeti nedeniyle sıklıkla tercih edilmektedir. zaman ve para tasarrufu sağladığı için etkili iletişim yoludur. maliyetinden kullanımının kolaylığından dolayı reklam yapmak isteyenler tarafından etkin şekilde kullan...

The quantity of textual data on the internet is growing exponentially, and it very tough task to obtain important relevant information from it. An efficient effective method required that provides a concise summary an article. This can be achieved by usage automatic text summarization. In this research, authors suggested approach for summarization where extractive generated methodology was modi...

We propose a novel text classification model, which aims to improve the performance of Arabic using machine learning techniques. One effective solutions in is find suitable feature selection method with an optimal number features alongside classifier. Although several methods have been proposed for language different techniques, such as methods, ensemble classifiers, and discriminative features...

Clustering of text documents is an important technique for documents retrieval. It aims to organize documents into meaningful groups or clusters. Preprocessing text plays a main role in enhancing clustering process of Arabic documents. This research examines and compares text preprocessing techniques in Arabic document clustering. It also studies effectiveness of text preprocessing techniques: ...

a r t i c l e i n f o Keywords: Hand gesture recognition Divergence fields Optical flow Maximum Stable Extremal Regions Term frequency-inverse document frequency (TF-IDF) Exemplar-based approaches for dynamic hand gesture recognition usually require a large collection of gestures to achieve high-quality performance. Efficient visual representation of the motion patterns hence is very important ...