Phạm Chuẩn - Academia.edu (original) (raw)

Papers by Phạm Chuẩn

Advances in intelligent systems and computing, 2018

Link prediction in an online social network aims to determine new interactions among its members ... more Link prediction in an online social network aims to determine new interactions among its members which are probably to arise in the near future. The previous researches dealt with the prediction task after calculating similarity scores between nodes in the link graph. New links are then predicted by implementing a supervised method from the scores. However, real-world applications often contain sparse and imbalanced data from the network, which may lead to difficulty in predicting new links. The selection of an appropriate classification method is indeed an important matter. Firstly, this paper proposes several extended metrics to calculate the similarity scores between nodes. Then, we design a new sampling method to make the training and testing data based on the data created by the extended metrics. Lastly, we assess some well-known classification methods namely J48, Weighted SVM, Gboost, Naive Bayes, Random Forest, Logistics Regressive, and Xgboost in order to choose the best method and equivalent environments for the link prediction problem. A number of open directions to the problem are suggested further.

Computer Science and Information Systems (FedCSIS), 2019 Federated Conference on, Feb 20, 2022

In recent years, it has been great interest for Question Answering (QA) systems applied to many a... more In recent years, it has been great interest for Question Answering (QA) systems applied to many areas placing a high value on the community. The study and development of such QA systems through chatbot tools in medicine raise great needs for clinicians in their daily activities. Chatbots use the knowledge that could be retrieved from a database, but with limited inference capability. In this paper, we propose a new QA system based on Knowledge Graph (knowledge graph) for Traditional Medicine. Data of the knowledge graph is obtained from two sources including those from diagnostic of treatment diagrams and those collected on well-known medical websites through the Internet. The knowledge graph is then formed by combining the entities and relationships using the Named Entity Recognition (NER) model. Diagnosis is made via the node similarity algorithm in the knowledge graph for symptom identification. The effectiveness of the system is demonstrated through theoretical analysis and real-world experimental outcomes.

In classification problems, the class imbalance significantly affectsthe efficiency of classifica... more In classification problems, the class imbalance significantly affectsthe efficiency of classification models. There are several proposals on improving SVM methods to adapt to imbalanced data sets. This paper proposes an improved SVM method for imbalanced data through adjusting weighted vector w, while combining with the Weighted-SVM training method, to increase the efficiency of classification for imbalanced data and apply to link prediction problem in co-authorship networks.

Journal of Computer Science and Cybernetics, Feb 27, 2020

Multi-attributes decision-making problem in dynamic neutrosophic environment is an open and highl... more Multi-attributes decision-making problem in dynamic neutrosophic environment is an open and highly-interesting research area with many potential applications in real life. The concept of the dynamic interval-valued neutrosophic set and its application for the dynamic decision-making are proposed recently, however the interdependence among criteria or preference is not dealt with in the proposed operations to well treat interdependence problems. Therefore, the definitions, mathematical operations and its properties are mentioned and discussed in detail. Then, Choquet integral-based distance between dynamic inteval-valued neutrosophic sets is defined and used to develop a new decision making model based on the proposed theory. A practical application of proposed approach is constructed and tested on the data of lecturers' performance collected from Vietnam National University (VNU) to illustrate the efficiency of new proposal.

Proceedings of the Seventh International Conference on Research in Intelligent and Computing in Engineering

Multimedia Tools and Applications

International Journal of Electrical and Computer Engineering (IJECE), 2022

Mobile ad-hoc networks (MANETs) is a set of mobile devices that can self-configuration, self-esta... more Mobile ad-hoc networks (MANETs) is a set of mobile devices that can self-configuration, self-established parameters to transmission in-network. Although limited inability, MANETs have been applied in many domains to serve humanity in recent years, such as disaster recovery, forest fire, military, intelligent traffic, or IoT ecosystems. Because of the movement of network devices, the system performance is low. In order to MANETs could more contribution in the future of the Internet, the routing is a significant problem to enhance the performance of MANETs. In this work, we proposed a new delay-based protocol aim enhance the system performance, called performance routing protocol based on delay (PRPD). In order to analyze the efficiency of the proposed solution, we compared the proposed protocol with traditional protocols. Experiment results showed that the PRPD protocol improved packet delivery ratio, throughput, and delay compared to the traditional protocols.

International Journal of Interactive Mobile Technologies (iJIM), 2021

This paper presents a modification of a well-known routing protocol, namely Ad hoc On-Demand Dist... more This paper presents a modification of a well-known routing protocol, namely Ad hoc On-Demand Distance Vector, as a solution to improve the performance of mobile ad hoc networks. We adapted the mobile agent technology as to novel metrics for routing in those networks. The metric is a function of the loss rate, the bandwidth and the end-to-end delay of the link. Indeed, we established a new tunable parameter to obtain a tradeoff between throughput and delay when computing the new metric. As a result, any routing protocol using this metric can al-ways choose a high-throughput and low-delay path between a source and a destination. Hence, the achievable performance of the mobile ad hoc networks has been improved remarkably with our modified routing protocol,

Applied Intelligence, Dec 5, 2017

Link prediction in online social networks is used to determine new interactions among its members... more Link prediction in online social networks is used to determine new interactions among its members which are likely to occur in the future. Link prediction in the coauthorship network has been regarded as one of the main targets in link prediction researches so far. Researchers have focused on analyzing and proposing solutions to give efficient recommendation for authors who can work together in a science project. In order to give precise prediction of

FAIR - NGHIÊN CỨU CƠ BẢN VÀ ỨNG DỤNG CÔNG NGHỆ THÔNG TIN 2015, 2016

Kỹ thuật lọc cộng tác (Collaborative Filtering-CF) là một kỹ thuật gợi ý phổ biến nhất được sử dụ... more Kỹ thuật lọc cộng tác (Collaborative Filtering-CF) là một kỹ thuật gợi ý phổ biến nhất được sử dụng nhiều trong các hệ thống gợi ý đã được tích hợp trong các website thương mại điện tử (chẳng hạn như amazon.com, barnesandnoble.com, Yahoo! news, TripAdvisor.com). Kỹ thuật CF dựa trên giả thiết rằng những người dùng (user) có cùng sở thích thì sẽ quan tâm một tập item tương tự. Phương pháp phân cụm lọc cộng tác (Iterative Clustered CF-ICCF) và lặp cộng tác tối ưu trọng số sử dụng thuật toán PSO (PSO-Feature Weighted) thể hiện tính hiệu quả cho hệ gợi ý mà giá trị đánh giá thuộc trong tập {1, 2,…, 5}. Tuy nhiên, các kỹ thuật đó không thể trực tiếp áp dụng cho các hệ thống gợi ý trong thực tế mà giá trị đánh giá trong tập {0, 1}. Do vậy, bài báo này đề xuất việc cải tiến hai phương pháp ICCF và PSO-Feature Weighted để có thể áp dụng được cho các hệ gợi ý mà giá trị đánh giá thuộc tập {0, 1}. Kết quả thực nghiệm của hai phương pháp mà chúng tôi đưa ra áp dụng trên bộ dữ liệu hệ gợi ý công việc cho thấy độ chính xác mô hình dự đoán có cải thiện rõ rệt so với phương pháp CF truyền thống đồng thời cũng giải quyết được vấn đề dữ liệu thưa mà phương pháp CF thường gặp phải. Từ khóa-Hệ thống gợi ý, kỹ thuật lọc cộng tác dựa trên Item, kỹ thuật lọc cộng tác dựa trên User, phân cụm lọc cộng tác, tối ưu trọng số lọc cộng tác, thuật toán tối ưu bầy đàn, phân cụm Spectral, thuật toán k-mean.

FAIR - NGHIÊN CỨU CƠ BẢN VÀ ỨNG DỤNG CÔNG NGHỆ THÔNG TIN - 2017, Aug 17, 2017

KỶ YẾU HỘI NGHỊ KHOA HỌC CÔNG NGHỆ QUỐC GIA LẦN THỨ XIII NGHIÊN CỨU CƠ BẢN VÀ ỨNG DỤNG CÔNG NGHỆ THÔNG TIN - Proceedings of the 13th National Conference on Fundamental & Applied Information Technology Research

Đại học Tài nguyên và Môi trường Hà Nội 2 Viện Công nghệ thông tin, Viện Hàn lâm Khoa học và Công... more Đại học Tài nguyên và Môi trường Hà Nội 2 Viện Công nghệ thông tin, Viện Hàn lâm Khoa học và Công nghệ Việt Nam 3 Đại học Thương mại 4 Viện Công nghệ thông tin, Đại học Quốc gia Hà Nội 5 Đại học Sư phạm kỹ thuật Hưng Yên