Conceptual Graphs Based Approach for Subjective Answers Evaluation

Author(s):  
Goonjan Jain ◽  
D.K. Lobiyal

Automated evaluation systems for objective type tests already exist. However, it is challenging to make an automated evaluation system for subjective type tests. Therefore, focus of this paper is on evaluation of simple text based subjective answers using Natural Language Processing techniques. A student's answer is evaluated by comparing it with a model answer of the question. Model answers cannot exactly match with the students' answers due to variability in writing. Therefore, researchers create conceptual graphs for both student as well as model answer and compute similarity between these graphs using techniques of graph similarity measures. Based on the similarity, marks are assigned to an answer. Lastly, in this manuscript authors compare the results obtained by human graders and the proposed system using Pearson correlation coefficient. Also, comparison has been drawn between the results of proposed system with other existing evaluation systems. The experimental evaluation of the proposed system shows promising results.

2020 ◽  
pp. 770-790
Author(s):  
Goonjan Jain ◽  
D.K. Lobiyal

Automated evaluation systems for objective type tests already exist. However, it is challenging to make an automated evaluation system for subjective type tests. Therefore, focus of this paper is on evaluation of simple text based subjective answers using Natural Language Processing techniques. A student's answer is evaluated by comparing it with a model answer of the question. Model answers cannot exactly match with the students' answers due to variability in writing. Therefore, researchers create conceptual graphs for both student as well as model answer and compute similarity between these graphs using techniques of graph similarity measures. Based on the similarity, marks are assigned to an answer. Lastly, in this manuscript authors compare the results obtained by human graders and the proposed system using Pearson correlation coefficient. Also, comparison has been drawn between the results of proposed system with other existing evaluation systems. The experimental evaluation of the proposed system shows promising results.


2017 ◽  
Vol 26 (2) ◽  
pp. 243-262
Author(s):  
Madhumitha Ramamurthy ◽  
Ilango Krishnamurthi

AbstractThe assessment of answers is an important process that requires great effort from evaluators. This assessment process requires high concentration without any fluctuations in mood. This substantiates the need to automate answer script evaluation. Regarding text answer evaluation, sentence similarity measures have been widely used to compare student written answers with reference texts. In this paper, we propose an automated answer evaluation system that uses our proposed cosine-based sentence similarity measures to evaluate the answers. Cosine measures have proved to be effective in comparing between free text student answers and reference texts. Here we propose a set of novel cosine-based sentence similarity measures with varied approaches of creating document vector space. In addition to this, we propose a novel synset-based word similarity measure for computation of document vectors coupled with varied approaches for dimensionality-reduction for reducing vector space dimensions. Thus, we propose 21 cosine-based sentence similarity measures and measured their performance using MSR paraphrase corpus and Li’s benchmark datasets. We also use these measures for automatic answer evaluation system and compare their performances using the Kaggle short answer and essay dataset. The performance of the system-generated scores is compared with the human scores using Pearson correlation. The results show that system and human scores have correlation between each other.


Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 298
Author(s):  
Kenta Kanakogi ◽  
Hironori Washizaki ◽  
Yoshiaki Fukazawa ◽  
Shinpei Ogata ◽  
Takao Okubo ◽  
...  

For effective vulnerability management, vulnerability and attack information must be collected quickly and efficiently. A security knowledge repository can collect such information. The Common Vulnerabilities and Exposures (CVE) provides known vulnerabilities of products, while the Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of common attributes and approaches employed by adversaries to exploit known weaknesses. Due to the fact that the information in these two repositories are not linked, identifying related CAPEC attack information from CVE vulnerability information is challenging. Currently, the related CAPEC-ID can be traced from the CVE-ID using Common Weakness Enumeration (CWE) in some but not all cases. Here, we propose a method to automatically trace the related CAPEC-IDs from CVE-ID using three similarity measures: TF–IDF, Universal Sentence Encoder (USE), and Sentence-BERT (SBERT). We prepared and used 58 CVE-IDs as test input data. Then, we tested whether we could trace CAPEC-IDs related to each of the 58 CVE-IDs. Additionally, we experimentally confirm that TF–IDF is the best similarity measure, as it traced 48 of the 58 CVE-IDs to the related CAPEC-ID.


2020 ◽  
Vol 7 (1) ◽  
pp. 46-53
Author(s):  
Rahmad Geri Kurniawan ◽  
Moch. Arif Bijaksana

The Qur'an is the Muslim holy book as the main source and guide, consisting of 114 surahs, 30 juz and has 6200 fewer verses in it. The search for relationships or arrangements of meaning between words in the Qur'an takes a long time to find and summarize. Obtained from the dictionary, encyclopedia, or thesaurus of the Al-Qur'an vocabulary, which contains each word entry has links with other words. This final project discusses the interrelations and semantic correspondence between words in the Qur'an, which supports to help find inter-related words in it, using linking with distributions that involve important parts in the word embedding. Measurement of the relevance of the word measurement with semantic similarity which is one of the lessons learned in Natural Language Processing (NLP). Extraordinary similarity measures the proximity of a word vector using cosine similarity. The process of converting words in the form of vectors using the fasttext which is the development of the Word2vec algorithm. The dataset is used for translations of the word Al-Qur'an in English and Indonesian. This entry becomes an input into the system then produces a score that represents the interrelationship between words. Evaluation of system output results is to perform performance calculations using Pearson correlation involving the gold standard.


2016 ◽  
Vol 1 (1) ◽  
pp. 1-15
Author(s):  
Frederich Oscar Lontoh

This research is titled " The influence of sermon, church music and church facilities on the level of attendance”. The purpose of research is to identify and analyze whether sermon, church music and church facilities have influence on the the level of attendance. The target population in this study is a Christian church members who live in the city of Surabaya.. Sample required is equal to 47 respondents. Through sampling stratified Random techniques.These influence was measured using Pearson correlation coefficient and multiple regression analysis, t-test and analysis of variance. Descriptive  analysis  were taken to analyze the level of attendance according to demographic groups.The hypothesis in this study are the sermon, church music and church facilities have positive and significant on the level of attendance. The results showed that collectively, there are positive and significant correlation among the sermon, church music and church facilities on the level of attendance  96,2%. It means that 96,2 % of level of attendance influenced by sermon, church music and church facilities and the other 28,9% by others. All of the variable partially have significant correlation to level of attendance.


2020 ◽  
Vol 16 (1) ◽  
pp. 47-53
Author(s):  
Vicente Benavides-Córdoba ◽  
Mauricio Palacios Gómez

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.


Author(s):  
María Leonila García Cedeño ◽  
Anicia Katherine Tarazona Meza ◽  
Robert Gonzalo Cedeño Mejía

Resilience is a phenomenon that can be studied in catastrophic situations but also in everyday matters such as disability, this being an alternative way of working in the environment that requires the adaptation of the social networks that contain and support people with this condition. The research was conducted at the Technical University of Manabí applied to the population of students with disabilities. The paper presents an analysis of support networks and their relationship with student resilience. The results related to the application of the Saavedra-Villalta test are shown, which allowed to correlate the level of resilience of the sample studied with the support networks. An analysis linked to the interpretation of the Pearson correlation coefficient is presented. The result obtained is presented by applying semi-structured interviews to a sample of 48 disabled students.


Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 204
Author(s):  
Charlyn Villavicencio ◽  
Julio Jerison Macrohon ◽  
X. Alphonse Inbaraj ◽  
Jyh-Horng Jeng ◽  
Jer-Guang Hsieh

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO’s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government’s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 156
Author(s):  
Charles Carlson ◽  
Vanessa-Rose Turpin ◽  
Ahmad Suliman ◽  
Carl Ade ◽  
Steve Warren ◽  
...  

Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms. Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters). Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/− 0.15), dP/dtmax (Pearson correlation coefficient of 0.51 +/− 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/− 0.17). Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume. Significance: To the best of the authors’ knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.


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