An Intelligent Grading System for Descriptive Examination Papers Based on Probabilistic Latent Semantic Analysis

Kim, Yu-Seop; Oh, JungSeok; Lee, Jae-Young; Chang, Jeong-Ho

doi:10.1007/978-3-540-30549-1_114

Cited by 5 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This results in a more principled approach with a solid foundation in statistical inference. PLSA has many applications, most prominently in information retrieval, natural language processing, machine learning from text, see e.g, [42][43][44][45]).…”

Section: Probabilistic Latent Semantic Analysis (Plsa)mentioning

confidence: 99%

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Holzinger

Schantl

Schroettner

et al. 2014

Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

View full text Add to dashboard Cite

Text is a very important type of data within the biomedical domain. For example, patient records contain large amounts of text which has been entered in a non-standardized format, consequently posing a lot of challenges to processing of such data. For the clinical doctor the written text in the medical findings is still the basis for decision makingneither images nor multimedia data. However, the steadily increasing volumes of unstructured information need machine learning approaches for data mining, i.e. text mining. This paper provides a short, concise overview of some selected text mining methods, focusing on statistical methods, i.e. Latent Semantic Analysis, Probabilistic Latent Semantic Analysis, Latent Dirichlet Allocation, Hierarchical Latent Dirichlet Allocation, Principal Component Analysis, and Support Vector Machines, along with some examples from the biomedical domain. Finally, we provide some open problems and future challenges, particularly from the clinical domain, that we expect to stimulate future research.

show abstract

Section: Probabilistic Latent Semantic Analysis (Plsa)mentioning

confidence: 99%

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Holzinger

Schantl

Schroettner

et al. 2014

Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

View full text Add to dashboard Cite

show abstract

“…For all these approaches, the recommendation of appropriate literature is a major issue and Recommender Systems (RS) are an alternative method of presenting and recovering knowledge from various resources and therefore a further step towards personalised e-learning systems (Khribi et al, 2009). In contrast to search engines, which deliver results from a user query, RS are focused on delivering unexpected results (Kim et al, 2004), which also support the pooling and sharing of information for informal learning (Linton and Schaefer, 2000). They even try to create recommendations for resources, whereas search engines are restricted in that regard due to limitations in automatic content analysis.…”

Section: Introduction and Motivation For Researchmentioning

confidence: 99%

Web analytics of user path tracing and a novel algorithm for generating recommendations in Open Journal Systems

Taraghi

Grossegger

Ebner

et al. 2013

Online Information Review

View full text Add to dashboard Cite

Purpose -The use of articles from scientific journals is an important part of research-based teaching at universities. The selection of relevant work from among the increasing amount of scientific literature can be problematic; the challenge is to find relevant recommendations, especially when the related articles are not obviously linked. This paper seeks to discuss these issues. Design/methodology/approach -This paper focuses on the analysis of user activity traces in journals using the open source software "Open Journal Systems" (OJS). The research questions to what extent end users follow a certain link structure given within OJS or immediately select the articles according to their interests. In the latter case, the recorded data sets are used for creating further recommendations. The analysis is based on an article matrix, displaying the usage frequency of articles and their user selected successive articles within the OJS. Furthermore, the navigation paths are analysed. Findings -It was found that the users tend to follow a set navigation structure. Moreover, a hybrid recommendation system for OJS is described, which uses content based filtering as the basic system extended by the results of a collaborative filtering approach. Originality/value -The paper presents two original contributions: the analysis of user path tracing and a novel algorithm that allows smooth integration of new articles into the existing recommendations, due to the fact that scientific journals are published in a frequent and regular time sequence.

show abstract

“…Al. [5] had developed an intelligent grading system, which scores descriptive examination papers automatically, based on Probabilistic Latent Semantic Analysis(PLSA) and it can acquire about 74% accuracy of a manual grading, 7% higher than that from the Simple Vector Space Model. Kang [6] designed and implemented a subjective-type evaluation system using syntactic and case-role information and the system results the 75% success rate.…”

Section: Introductionmentioning

confidence: 99%

A Scoring System for Short Answers on the Test in a Large Group

Lee

2012

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Abstract. In this paper, we have developed the scoring system that scores short answers based on the score table updated by average scores of non-existing answers. The accuracy and the consistency are very important, because the score influences a life. Automatic mark systems have consistency but need more accuracy. In the paper and pencil, a consistency is difficult to maintain. To achieve accuracy and consistency, the scoring system consists of three passes. The first pass is to score the applicant's answers based on the readymade score table if it is in the table. If not, the second pass updates the table with the average of credits for which committee members evaluate the nonexisting answer. Finally, the third pass is to score non-existing answer based on the updated table.

show abstract

An Intelligent Grading System for Descriptive Examination Papers Based on Probabilistic Latent Semantic Analysis

Cited by 5 publications

References 4 publications

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Web analytics of user path tracing and a novel algorithm for generating recommendations in Open Journal Systems

A Scoring System for Short Answers on the Test in a Large Group

Contact Info

Product

Resources

About