A Strategy Oriented , Machine Learning Approach to Automatic Quality Assessment
نویسنده
چکیده
A Strategy Oriented, Machine Learning Approach to Automatic Quality Assessment of Wikipedia Articles Gabriel De La Calzada This work discusses an approach to modeling and measuring information quality of Wikipedia articles. The approach is based on the idea that the quality of Wikipedia articles with distinctly different profiles needs to be measured using different information quality models. To implement this approach, a software framework written in the Java language was developed to collect and analyze information of Wikipedia articles. We report on our initial study, which involved two categories of Wikipedia articles: ”stabilized” (those, whose content has not undergone major changes for a significant period of time) and ”controversial” (articles that have undergone vandalism, revert wars, or whose content is subject to internal discussions between Wikipedia editors). In addition, we present simple information quality models and compare their performance on a subset of Wikipedia articles with the information quality evaluations provided by human users. Our experiment shows that using special-purpose models for information quality captures user sentiment about Wikipedia articles better than using a single model for both categories of articles.
منابع مشابه
A Machine Learning Approach to No-Reference Objective Video Quality Assessment for High Definition Resources
The video quality assessment must be adapted to the human visual system, which is why researchers have performed subjective viewing experiments in order to obtain the conditions of encoding of video systems to provide the best quality to the user. The objective of this study is to assess the video quality using image features extraction without using reference video. RMSE values and processing ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملExplain the theoretical and practical model of automatic facade design intelligence in the process of implementing the rules and regulations of facade design and drawing
Artificial intelligence has been trying for decades to create systems with human capabilities, including human-like learning; Therefore, the purpose of this study is to discover how to use this field in the process of learning facade design, specifically learning the rules and standards and national regulations related to the design of facades of residential buildings by machine with a machine ...
متن کامل