User stories play an important role in agile development systems. In this study, a method of summarising user stories is proposed to reuse them in the future. To enhance the results, quality improvement should be made on user stories. It would help developers build better results, and it may also lead to omitting some essential information. To avoid such issues, user stories are duplicated in two exact similar groups, and quality improvement is made on one set while the other set remains unattained. With the help of a modified bag of words and a verb parser, a collection of keywords and key verbs are extracted for both groups. Afterwards, automatic user stories are made, and then an expert improves them. Next, some experts choose between the results and select the better ones. The result is evaluated by applying different experiments on the framework and prototype implementation on 14 data sets of a user story from industry and a fake data set from Duke University. The result showed 97% of micro F ‐measure and 93% of macro F ‐measure, which are promising. These new user stories can be used as the base user stories in future similar projects.
Due to the increase of video data generated in today's life, finding ways to mine these data or summarize them has become a great challenge. Thus, the main objective of this work is to investigate why video summarization is needed and how it could be done in the best possible way. To meet this goal, a systematic literature review (SLR) was conducted on articles published from 2020 to 2021 to identify the primary studies on the use of video skimming in data mining, following a predefined review protocol. The contributions and the types of evidence reported regarding the benefits of this method were also examined. In summary, the main findings of this work are: (1) the use of video summarization is widely variant, and more new domains are being introduced each year, (3) industrial researchers have not participated in academic studies, and (4) different evaluation metrics and datasets have been introduced, and studies are attempting to introduce new methods. Finally, this work showed several promising research opportunities that are pretty important and interesting but underexplored in current research and practice.
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