Review on knowledge extraction from text and scope in agriculture domain

Mol, E A Nismi; Kumar, Mukesh

doi:10.1007/s10462-022-10239-9

Cited by 5 publications

(2 citation statements)

References 109 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the application areas, data extraction techniques help to extract a huge amount of data. Improvement in technology and the rise of artificial intelligence impact the efficiency of these techniques and enable more accurate knowledge extraction (Nismi Mol & Santosh Kumar, 2023). Most NLP applications in education focus on the automated assessment of essays and open-ended questions.…”

Section: Research In the Fields Of Educational Data Mining And Learni...mentioning

confidence: 99%

“…Thus, to process this information by a computer or machine in various applications, it needs to be in a structured format. Knowledge extraction refers to such a process when relevant information from the unstructured data is extracted and represented in a structured form (Nismi Mol & Santosh Kumar, 2023). Data mining and knowledge extraction together allow one to gain more insight for the fields in which they are applied.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Educational Data Mining and Learning Analytics: Text Generators Usage Effect on Students’ Grades

Pliuskuvienė,

Radvilaitė,

Juodagalvytė

et al. 2024

New Trends in Computer Sciences

View full text Add to dashboard Cite

Today, various types of data are constantly growing, so they can be used for different purposes. In this investigation, educational data has been analyzed to determine the influence of assessment on student knowledge. The newly collected dataset has been prepared and statistically analyzed. The dataset consists of open-question answers collected on one study subject during the midterm exam at Vilnius Gediminas Technical University. The results of the statistical analysis have shown that by using the text generators, students obtained higher grades by paraphrasing the answers to the questions in good quality. Furthermore, research has shown which types of questions are more difficult for students to answer without additional material and using text generation tools. It can be useful for lecturers planning course assessment tasks.

show abstract

Section: Research In the Fields Of Educational Data Mining And Learni...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%