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3 results for “Task Mining”
Large Dataset of Nigeria Covid-19 Tweets for Sentiment Analysis and Opinion Mining Tasks
<p><strong>Background</strong></p> <p>Information is essential for growth; without it, little can be accomplished. Data gathering has seen significant changes throughout the previous few centuries because of certain transitory medium. The look and style of information transference are affected by the employment of new and emerging technologies, some of which are efficient, others are reliable, and many more are quick and effective, but a few were disappointing for various reasons.</p> <p><strong>Aims</strong></p> <p>This study aims at using TextBlob and VADER analyser with historical tweets, to analyse emotional responses to the corona virus pandemic (covid-19). It shows us how much of a sociological, environmental, and economic impact it has in Nigeria, among other things. This study would be a tremendous step forward for students, researchers, and scholars who want to advance in fields like data science, machine learning, and deep learning.</p> <p><strong>Methodology</strong></p> <p>The hashtag ‘covid-19' was used to collect 1,048,575 tweets from Twitter. The tweets were pre-processed with a twitter tokenizer, and Valence Aware Dictionary for Sentiment Reasoning (VADER) and TextBlob were used for sentiment and text mining, respectively. Topic modelling was done with Latent Dirichlet Allocation (LDA). The simulated subjects, on the other hand, were visualized using Multidimensional scaling (MDS).</p> <p><strong>Results</strong></p> <p>The result of the VADER sentiment returned 39.8%, 31.3% and 28.9%, positive, neutral, and negative sentiment respectively while the result of the TextBlob sentiment returned 46.0%, 36.7% and 17.3%, neutral, positive, and negative sentiment, respectively.</p> <p><strong>Conclusion</strong></p> <p>With all of this, information from social media may be used to help organizations, governments, and nations around the world make smart and effective decisions about how to restrict and limit the negative effects of covid-19. Also know the opinion and challenges of people, then deal with problem of misinformation.</p> <p>It is concluded that with popular belief a significant number of the populace regards covid-19 as a virus that has come to stay, some believe it will eventually be conquered.</p>
Performance of GPT-4o mini and GPT-4o for medical text mining tasks at different temperature settings
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[Research Data] Mining Relevant Solutions for Programming Tasks from Search Engine Results
<p>[Abstract]</p> <p>Software development is a knowledge-intensive activity. Official documentation for developers may not be sufficient for all developer needs. Searching for information on the Internet is a usual practice, but finding really useful information may be challenging, because the best solutions are not always among the first ranked pages. So, developers have to read and discard irrelevant pages, that is, pages that do not have code examples or that have content with little focus on the desired solution. This work aims at proposing an approach to mine relevant solutions for programming tasks from search engine results that remove irrelevant pages. The approach works as follows: a query related to the programming task is prepared, and given as an input to a search engine. The returned pages pass through an automatic filter to select relevant pages. We evaluated the top-20 pages returned by the Google search engine, for 10 different queries, and observed that only 31\% of the evaluated pages are relevant to developers. Then, we proposed and evaluated three different approaches to mine the relevant pages returned by the search engine. Google’s search engine has been used as a baseline, and our results have shown that Google’s search engine returns a reasonable number of irrelevant pages for developers, and we could find an effective approach to remove irrelevant pages, suggesting that developers could benefit from a customized web search filter for development content.</p> <p>[Contents of Research Data.rar file]</p> <p>The Research Data.rar file has a folder called Research Data that contains 3 folders internally, with the names: “01 – Source Code”, “02 - Data” and “03 – Preprocessing rules”. The folder “01 – Source Code” contains the JAVA source code of the implementations of the proposed approaches. The folder “02 - Data” contains the data of the evaluations carried out in the work, which are in the folders “01 - Evaluation results of pages returned by Google” and “02 - Results of approaches comparisons”. The folder “01 - Evaluation results of pages returned by Google” has the evaluations carried out on the first 20 pages returned by Google, following the criteria defined in the work, for the 10 queries considered in the evaluation. The folder “02 - Results of approaches comparisons” contains the results of the evaluation of the proposed approaches, for the 10 queries considered in the evaluation. In this evaluation, the number of pages given as input for the approaches was increased from 3 to 20 pages, for each number of pages a folder was generated with the results. In addition to the results of the Precision, Recall and F-Measure metrics that are in the file named Results Approaches.txt, other files were generated for analysis. For example, the Instances_without_outliers.txt file shows which pages were filtered out after applying the outlier page removal filter. The Selected Pages Approach 4.txt file, on the other hand, shows which pages were filtered after applying the filters of the GORCUO approach. The folder “03 - Preprocessing rules” has a file called Rules.java. In this file, there is the commented JAVA source code, from the implementation of the rules created in the pre-processing stage of the proposed approach.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.