找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Requirements Engineering: Foundation for Software Quality; 29th International W Alessio Ferrari,Birgit Penzenstadler Conference proceedings

[復(fù)制鏈接]
樓主: 退縮
11#
發(fā)表于 2025-3-23 12:57:13 | 只看該作者
12#
發(fā)表于 2025-3-23 15:23:41 | 只看該作者
13#
發(fā)表于 2025-3-23 19:53:25 | 只看該作者
14#
發(fā)表于 2025-3-23 22:25:49 | 只看該作者
Using Language Models for?Enhancing the?Completeness of?Natural-Language Requirementstively discovering omissions in requirements and the level of noise in the predictions. Our second contribution is devising a machine learning-based filter that post-processes predictions made by BERT to further reduce noise. We empirically evaluate our solution over 40 requirements specifications d
15#
發(fā)表于 2025-3-24 05:45:55 | 只看該作者
Requirement or?Not, That?is the?Question: A Case from?the?Railway Industryhow that the transformer-based BERT classifier performs the best, with an average F1 score of 0.82 and 0.87 on industrial and public datasets, respectively. Our results also confirm that few-shot classifiers can achieve comparable results with an average F1 score of 0.76 on significantly lower sampl
16#
發(fā)表于 2025-3-24 10:15:26 | 只看該作者
17#
發(fā)表于 2025-3-24 14:15:40 | 只看該作者
18#
發(fā)表于 2025-3-24 18:07:04 | 只看該作者
Requirements Classification Using FastText and?BETO in?Spanish Documentsataset, but BETO outperformed other classifiers on prediction performance in a dataset with different origins. .: Our evaluation provides a quantitative analysis of the classification performance of fastTest and BETO in comparison with ML/DL algorithms, the external validity of trained models on ano
19#
發(fā)表于 2025-3-24 21:04:02 | 只看該作者
Exploring Requirements for?Software that?Learns: A Research Previewunique characteristics of software requirements that are specific to ML components. To this end, we collect and examine requirements from both academic and industrial sources. . To the best of our knowledge, this is the first work that presents real-life, industrial patterns of requirements for ML c
20#
發(fā)表于 2025-3-25 00:27:01 | 只看該作者
An Investigation of?Challenges Encountered When Specifying Training Data and?Runtime Monitors for?Saovides a list of the identified underlying challenges related to the difficulties practitioners experience when specifying training data and runtime monitoring for ML models. Furthermore, interconnection between the challenges were found and based on these connections recommendation proposed to over
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-20 06:44
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
保德县| 杨浦区| 苏州市| 罗甸县| 临西县| 广南县| 红安县| 咸阳市| 博罗县| 客服| 色达县| 汤阴县| 瓦房店市| 庆城县| 夏河县| 扶风县| 睢宁县| 体育| 汤阴县| 双桥区| 中阳县| 阳春市| 涿鹿县| 文成县| 昂仁县| 西青区| 商水县| 雅安市| 广灵县| 宜阳县| 长寿区| 阿合奇县| 晋宁县| 五台县| 东至县| 洪湖市| 彭泽县| 监利县| 慈利县| 文山县| 黔东|