Ontologies have become the effective modeling for various applications and significantly in the semantic web. The difficulty of extracting information from the web, which was created mainly for visualising information, has driven the birth of the semantic web, which will contain much more resources than the web and will attach machine-readable semantic information to these resources. Ontologica...

Agile projects typically employ just-in-time requirements engineering and record their requirements (socalled feature requests) in an issue tracker. In open source projects we observed large networks of feature requests that are linked to each other. Both when trying to understand the current state of the system and to understand how a new feature request should be implemented, it is important ...

It is usually true that some structures like title can express the main content of texts, and these structures may have an influence on the effectiveness of text categorization. However, the most common feature weighting algorithms, called term frequency-inverse document frequency (TF-IDF) doesn’t think about the structural information of texts. To solve this problem, a new feature weighting al...

Abstract The goal of our research is improvement mathematics curriculum and popularization among students economics in developing countries. We analyze compare curricula pure courses that are taught to university faculties Japan Bosnia Herzegovina. Data set contains math syllabuses 2021/22 school year from six public universities Herzegovina seven Japan. text corpus was pre-processed then the T...

Phishing is one of the luring techniques used to exploit personal information. A phishing webpage detection system (PWDS) extracts features to determine whether it is a phishing webpage or not. Selecting appropriate features improves the performance of PWDS. Performance criteria are detection accuracy and system response time. The major time consumed by PWDS arises from feature extraction that ...

In this paper, we study one semi-supervised and several supervised methods for extractive query-focused multi-document summarization. Traditional approaches to multidocument summarization are either unsupervised or supervised. The unsupervised approaches use heuristic rules to select the most important sentences, which are hard to generalize. On the other hand, huge amount of annotated data is ...

Text categorization is one of the well studied problems in data mining and information retrieval. Given a large quantity of documents in a data set where each document is associated with its corresponding category. Categorization involves building a model from classified documents, in order to classify previously unseen documents as accurately as possible. In this paper, we investigate variatio...

To achieve carbon neutrality by 2050, Korea has been expanding its investment in renewal energy distribution and technology development. However, with this rapid expansion of renewable energy, public concern about it grown. This study developed used a big data analysis-based procedure to analyze the questions registered on Naver, largest portal site Korea, from 2008 2020 identify over energy. T...

Automatic summarization <span>is a technique for quickly introducing key information by abbreviating large sections of material. Summarization may apply to text and video with different method display the abstract subject. Natural language processing is employed in automated this research, which applies YouTube videos transcribing applying summary stages study. Based on number words sente...

COVID-19 is an infectious disease caused by a newly discovered type of coronavirus. Based on recommendations from the Technical Advisory Group Virus Evolution, WHO established new variant called Omicron. Due to rapid spread COVID-19, booster vaccine was created deal with virus variant. However, strategy giving vaccines that never ends considered controversial community, and this shown number pe...