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Full-Text Articles in Physical Sciences and Mathematics
Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Lin
Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Lin
Research Collection School Of Computing and Information Systems
Education institutions collect feedback from students upon course completion and analyse it to improve curriculum design, delivery methodology and students' learning experience. A large part of feedback comes in the form textual comments, which pose a challenge in quantifying and deriving insights. In this paper, we present a novel approach of the Latent Dirichlet Allocation (LDA) model to address this difficulty in handling textual student feedback. The analysis of quantitative part of student feedback provides generalratings and helps to identify aspects of the teaching that are successful and those that can improve. The reasons for the failure or success, however, …
Categorizing The Content Of Github Readme Files, Gede Artha Azriadi Prana, Christoph Treude, Ferdian Thung, Thushari Atapattu, David Lo
Categorizing The Content Of Github Readme Files, Gede Artha Azriadi Prana, Christoph Treude, Ferdian Thung, Thushari Atapattu, David Lo
Research Collection School Of Computing and Information Systems
README files play an essential role in shaping a developer’s first impression of a software repository and in documenting the software project that the repository hosts. Yet, we lack a systematic understanding of the content of a typical README file as well as tools that can process these files automatically. To close this gap, we conduct a qualitative study involving the manual annotation of 4,226 README file sections from 393 randomly sampled GitHub repositories and we design and evaluate a classifier and a set of features that can categorize these sections automatically. We find that information discussing the ‘What’ and …
Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points, Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi
Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points, Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Locally Linear Support Vector Machine (LLSVM) has been actively used in classification tasks due to its capability of classifying nonlinear patterns. However, existing LLSVM suffers from two drawbacks: (1) a particular and appropriate regularization for LLSVM has not yet been addressed; (2) it usually adopts a three-stage learning scheme composed of learning anchor points by clustering, learning local coding coordinates by a predefined coding scheme, and finally learning for training classifiers. We argue that this decoupled approaches oversimplifies the original optimization problem, resulting in a large deviation due to the disparate purpose of each step. To address the first issue, …