Chien D.C. Ta

Nhà nghiên cứu Hồ sơ 6/10

Trường Đại học Công nghiệp TP.HCM · Công nghệ Thông tin

17 công bố · 36 trích dẫn · h-index 3

Thông tin

🏛️Nơi công tác: Trường Đại học Công nghiệp TP.HCM
🔬Lĩnh vực: Công nghệ Thông tin
🆔ORCID: 0000-0003-1378-752X
✍️Hồ sơ chưa đầy đủ — bổ sung thông tin

Công bố tiêu biểu

W-PathSim: Novel Approach of Weighted Similarity Measure in Content-Based Heterogeneous Information Networks by Applying LDA Topic Modeling9 trích dẫn
Lecture notes in computer science · 2018 · DOI

Improving the formal concept analysis algorithm to construct domain ontology4 trích dẫn
· 2012 · DOI

Identifying semantic and syntactic relations from text documents4 trích dẫn
· 2015 · DOI

Simplified effective method for identifying semantic relations from a knowledge graph3 trích dẫn
Journal of Intelligent & Fuzzy Systems · 2022 · DOI

Automatic Extraction of Semantic Relations from Text Documents3 trích dẫn
Lecture notes in computer science · 2016 · DOI

Constructing a subject-based ontology through the utilization of a semantic knowledge graph3 trích dẫn
International Journal of Information Technology · 2023 · DOI

Automatic Evaluation of the Computing Domain Ontology2 trích dẫn
Lecture notes in computer science · 2015 · DOI

GOW-LDA: Applying Term Co-occurrence Graph Representation in LDA Topic Models Improvement2 trích dẫn
Lecture notes in electrical engineering · 2018 · DOI

Improving the Algorithm for Mapping of OWL to Relational Database Schema1 trích dẫn
Lecture notes in computer science · 2015 · DOI

Automatic topic labelling for text document using ontology of graph-based concepts and dependency graph1 trích dẫn
International Journal of Business Information Systems · 2021 · DOI

Về lĩnh vực Công nghệ Thông tin

2.378học giả

36.643công bố

398.190trích dẫn

3.7h-index trung bình

Hướng nghiên cứu phổ biến trong lĩnh vực:

Topic ModelingNatural Language Processing TechniquesAdvanced Neural Network ApplicationsNetwork Security and Intrusion DetectionMultimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Nơi có nhiều học giả lĩnh vực này nhất: