Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Software Engineering
Title: App Review Analysis Via Active Learning: Reducing Supervision Effort without Compromising Classification Accuracy
Abstract: Automated app review analysis is an important avenue for extracting a variety of requirements-related information. Typically, a first step toward performing such analysis is preparing a training dataset, where developers (experts) identify a set of reviews and, manually, annotate them according to a given task. Having sufficiently large training data is important for both achieving a high prediction accuracy and avoiding overfitting. Given millions of reviews, preparing a training set is laborious. We propose to incorporate active learning, a machine learning paradigm, in order to reduce the human effort involved in app review analysis. Our app review classification framework exploits three active learning strategies based on uncertainty sampling. We apply these strategies to an existing dataset of 4,400 app reviews for classifying app reviews as features, bugs, rating, and user experience. We find that active learning, compared to a training dataset chosen randomly, yields a significantly higher prediction accuracy under multiple scenarios.
Extracted statement — Utilities in CrowdRE: Task
Research field: Software Engineering
Title: Discovering Requirements through Goal-Driven Process Mining
Abstract: Software systems are designed to support their users in performing tasks that are parts of more general processes. Unfortunately, software designers often make invalid assumptions about the users' processes and therefore about the requirements to support such processes. Eliciting and validating such assumptions through manual means (e.g., through observations, interviews, and workshops) is expensive, time-consuming, and may fail to identify the users' real processes. Using process mining may reduce these problems by automating the monitoring and discovery of the actual processes followed by a crowd of users. The Crowd provides an opportunity to involve diverse groups of users to interact with a system and conduct their intended processes. This implicit feedback in the form of discovered processes can then be used to modify the existing system's functionalities and ensure whether or not a software product is used as initially designed. In addition, the analysis of user-system interactions may reveal lacking functionalities and quality issues. These ideas are illustrated on the GreenSoft personal energy management system.
Extracted statement — Utilities in CrowdRE: Task
Research field: Software Engineering
Title: Software Feature Request Detection in Issue Tracking Systems
Abstract: Communication about requirements is often handled in issue tracking systems, especially in a distributed setting. As issue tracking systems also contain bug reports or programming tasks, the software feature requests of the users are often difficult to identify. This paper investigates natural language processing and machine learning features to detect software feature requests in natural language data of issue tracking systems. It compares traditional linguistic machine learning features, such as "bag of words", with more advanced features, such as subject-action-object, and evaluates combinations of machine learning features derived from the natural language and features taken from the issue tracking system meta-data. Our investigation shows that some combinations of machine learning features derived from natural language and the issue tracking system meta-data outperform traditional approaches. We show that issues or data fields (e.g. descriptions or comments), which contain software feature requests, can be identified reasonably well, but hardly the exact sentence. Finally, we show that the choice of machine learning algorithms should depend on the goal, e.g. maximization of the detection rate or balance between detection rate and precision. In addition, the paper contributes a double coded gold standard and an open-source implementation to further pursue this topic.
Extracted statement — Utilities in CrowdRE: Task
Research field: Software Engineering
Title: Supporting Requirements Elicitation by Tool-Supported Video Analysis
Abstract: Workshops are an established technique for requirements elicitation. A lot of information is revealed during a workshop, which is generally captured via textual minutes. The scribe suffers from a cognitive overload due to the difficulty of gathering all information, listening and writing at the same time. Video recording is used as additional option to capture more information, including non-verbal gestures. Since a workshop can take several hours, the recorded video will be long and may be disconnected from the scribe's notes. Therefore, the weak and unclear structure of the video complicates the access to the recorded information, for example in subsequent requirements engineering activities. We propose the combination of textual minutes and video with a software tool. Our objective is connecting textual notes with the corresponding part of the video. By highlighting relevant sections of a video and attaching notes that summarize those sections, a more useful structure can be achieved. This structure allows an easy and fast access to the relevant information and their corresponding video context. Thus, a scribe's overload can be mitigated and further use of a video can be simplified. Tool-supported analysis of such an enriched video can facilitate the access to all communicated information of a workshop. This allows an easier elicitation of high-quality requirements. We performed a preliminary evaluation of our approach in an experimental set-up with 12 participants. They were able to elicit higher-quality requirements with our software tool.
Extracted statement — Has research method: Experiment
Research field: Terrestrial and Aquatic Ecology
Title: Alien plants can be associated with a decrease in local and regional native richness even when at low abundance
Abstract: The impacts of alien plants on native richness are usually assessed at small spatial scales and in locations where the alien is at high abundance. But this raises two questions: to what extent do impacts occur where alien species are at low abundance, and do local impacts translate to effects at the landscape scale? In an analysis of 47 widespread alien plant species occurring across a 1,000 km2 landscape, we examined the relationship between their local abundance and native plant species richness in 594 grassland plots. We first defined the critical abundance at which these focal alien species were associated with a decline in native α‐richness (plot‐scale species numbers), and then assessed how this local decline was translated into declines in native species γ‐richness (landscape‐scale species numbers). After controlling for sampling biases and environmental gradients that might lead to spurious relationships, we found that eight out of 47 focal alien species were associated with a significant decline in native α‐richness as their local abundance increased. Most of these significant declines started at low to intermediate classes of abundance. For these eight species, declines in native γ‐richness were, on average, an order of magnitude (32.0 vs. 2.2 species) greater than those found for native α‐richness, mostly due to spatial homogenization of native communities. The magnitude of the decrease at the landscape scale was best explained by the number of plots where an alien species was found above its critical abundance. Synthesis. Even at low abundance, alien plants may impact native plant richness at both local and landscape scales. Local impacts may result in much greater declines in native richness at larger spatial scales. Quantifying impact at the landscape scale requires consideration of not only the prevalence of an alien plant, but also its critical abundance and its effect on native community homogenization. This suggests that management approaches targeting only those locations dominated by alien plants might not mitigate impacts effectively. Our integrated approach will improve the ranking of alien species risks at a spatial scale appropriate for prioritizing management and designing conservation policies.
Extracted statement — Ecological Level of evidence: Community
Research field: Terrestrial and Aquatic Ecology
Title: Alien plants can be associated with a decrease in local and regional native richness even when at low abundance
Abstract: The impacts of alien plants on native richness are usually assessed at small spatial scales and in locations where the alien is at high abundance. But this raises two questions: to what extent do impacts occur where alien species are at low abundance, and do local impacts translate to effects at the landscape scale? In an analysis of 47 widespread alien plant species occurring across a 1,000 km2 landscape, we examined the relationship between their local abundance and native plant species richness in 594 grassland plots. We first defined the critical abundance at which these focal alien species were associated with a decline in native α‐richness (plot‐scale species numbers), and then assessed how this local decline was translated into declines in native species γ‐richness (landscape‐scale species numbers). After controlling for sampling biases and environmental gradients that might lead to spurious relationships, we found that eight out of 47 focal alien species were associated with a significant decline in native α‐richness as their local abundance increased. Most of these significant declines started at low to intermediate classes of abundance. For these eight species, declines in native γ‐richness were, on average, an order of magnitude (32.0 vs. 2.2 species) greater than those found for native α‐richness, mostly due to spatial homogenization of native communities. The magnitude of the decrease at the landscape scale was best explained by the number of plots where an alien species was found above its critical abundance. Synthesis. Even at low abundance, alien plants may impact native plant richness at both local and landscape scales. Local impacts may result in much greater declines in native richness at larger spatial scales. Quantifying impact at the landscape scale requires consideration of not only the prevalence of an alien plant, but also its critical abundance and its effect on native community homogenization. This suggests that management approaches targeting only those locations dominated by alien plants might not mitigate impacts effectively. Our integrated approach will improve the ranking of alien species risks at a spatial scale appropriate for prioritizing management and designing conservation policies.
Extracted statement — Investigated species: plants
Research field: Terrestrial and Aquatic Ecology
Title: Effects of grazing and climate warming on plant diversity, productivity and living state in the alpine rangelands and cultivated grasslands of the Qinghai-Tibetan Plateau
Abstract: Overgrazing and climate warming may be important drivers of alpine rangeland degradation in the Qinghai-Tibetan Plateau (QTP). In this study, the effects of grazing and experimental warming on the vegetation of cultivated grasslands, alpine steppe and alpine meadows on the QTP were investigated. The three treatments were a control, a warming treatment and a grazing treatment and were replicated three times on each vegetation type. The warming treatment was applied using fibreglass open-top chambers and the grazing treatment was continuous grazing by yaks at a moderately high stocking rate. Both grazing and warming negatively affected vegetation cover. Grazing reduced vegetation height while warming increased vegetation height. Grazing increased but warming reduced plant diversity. Grazing decreased and warming increased the aboveground plant biomass. Grazing increased the preferred forage species in native rangelands (alpine steppe and alpine meadow), while warming increased the preferred forage species in the cultivated grassland. Grazing reduced the vegetation living state (VLS) of all three alpine grasslands by nearly 70%, while warming reduced the VLS of the cultivated grassland and the alpine steppe by 32% and 56%, respectively, and promoted the VLS of the alpine meadow by 20.5%. It was concluded that overgrazing was the main driver of change to the alpine grassland vegetation on the QTP. The findings suggest that grazing regimes should be adapted in order for them to be sustainable in a warmer future.
Extracted statement — Experimental treatment: Warming
Research field: Terrestrial and Aquatic Ecology
Title: Effects of grazing and climate warming on plant diversity, productivity and living state in the alpine rangelands and cultivated grasslands of the Qinghai-Tibetan Plateau
Abstract: Overgrazing and climate warming may be important drivers of alpine rangeland degradation in the Qinghai-Tibetan Plateau (QTP). In this study, the effects of grazing and experimental warming on the vegetation of cultivated grasslands, alpine steppe and alpine meadows on the QTP were investigated. The three treatments were a control, a warming treatment and a grazing treatment and were replicated three times on each vegetation type. The warming treatment was applied using fibreglass open-top chambers and the grazing treatment was continuous grazing by yaks at a moderately high stocking rate. Both grazing and warming negatively affected vegetation cover. Grazing reduced vegetation height while warming increased vegetation height. Grazing increased but warming reduced plant diversity. Grazing decreased and warming increased the aboveground plant biomass. Grazing increased the preferred forage species in native rangelands (alpine steppe and alpine meadow), while warming increased the preferred forage species in the cultivated grassland. Grazing reduced the vegetation living state (VLS) of all three alpine grasslands by nearly 70%, while warming reduced the VLS of the cultivated grassland and the alpine steppe by 32% and 56%, respectively, and promoted the VLS of the alpine meadow by 20.5%. It was concluded that overgrazing was the main driver of change to the alpine grassland vegetation on the QTP. The findings suggest that grazing regimes should be adapted in order for them to be sustainable in a warmer future.
Extracted statement — Study type: Experiment
Research field: Theory, Knowledge and Science
Title: Knowledge Graph Refinement: A Survey of Approaches and Evaluation Methods
Abstract: In the recent years, different Web knowledge graphs, both free and commercial, have been created. While Google coined the term "Knowledge Graph" in 2012, there are also a few openly available knowledge graphs, with DBpedia, YAGO, and Freebase being among the most prominent ones. Those graphs are often constructed from semi-structured knowledge, such as Wikipedia, or harvested from the web with a combination of statistical and linguistic methods. The result are large-scale knowledge graphs that try to make a good trade-off between completeness and correctness. In order to further increase the utility of such knowledge graphs, various refinement methods have been proposed, which try to infer and add missing knowledge to the graph, or identify erroneous pieces of information. In this article, we provide a survey of such knowledge graph refinement approaches, with a dual look at both the methods being proposed as well as the evaluation methodologies used.
Extracted statement — Has evaluation: Methods
Research field: Theory, Knowledge and Science
Title: Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web
Abstract: The increasingly pervasive nature of the Web, expanding to devices and things in everyday life, along with new trends in Artificial Intelligence call for new paradigms and a new look on Knowledge Representation and Processing at scale for the Semantic Web. The emerging, but still to be concretely shaped concept of "Knowledge Graphs" provides an excellent unifying metaphor for this current status of Semantic Web research. More than two decades of Semantic Web research provides a solid basis and a promising technology and standards stack to interlink data, ontologies and knowledge on the Web. However, neither are applications for Knowledge Graphs as such limited to Linked Open Data, nor are instantiations of Knowledge Graphs in enterprises – while often inspired by – limited to the core Semantic Web stack. This report documents the program and the outcomes of Dagstuhl Seminar 18371 "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web", where a group of experts from academia and industry discussed fundamental questions around these topics for a week in early September 2018, including the following: what are knowledge graphs? Which applications do we see to emerge? Which open research questions still need be addressed and which technology gaps still need to be closed?
Extracted statement — Has result: Seminar
Research field: Urban Studies
Title: Incremental development of a shared urban ontology: the Urbamet experience
Abstract: Thesauri are used for document referencing. They define hierarchies of domains. We show how document and domain contents can be used to validate and update a classification based on a thesaurus. We use document indexing and classification techniques to automate these operations. We also draft a methodology to systematically address those issues. Our techniques are applied to Urbamet, a thesaurus in the field of town planning.
Extracted statement — Ontology type: Thesaurus
Research field: Urban Studies
Title: Incremental development of a shared urban ontology: the Urbamet experience
Abstract: Thesauri are used for document referencing. They define hierarchies of domains. We show how document and domain contents can be used to validate and update a classification based on a thesaurus. We use document indexing and classification techniques to automate these operations. We also draft a methodology to systematically address those issues. Our techniques are applied to Urbamet, a thesaurus in the field of town planning.
Extracted statement — Ontology name: Urbamet
Research field: Urban Studies and Planning
Title: Skunkworks finder: unlocking the diversity advantage of urban innovation ecosystems
Abstract: Entrepreneurs and start-up founders using innovation spaces and hubs often find themselves inside a filter bubble or echo chamber, where like-minded people tend to come up with similar ideas and recommend similar approaches to innovation. This trend towards homophily and a polarisation of like-mindedness is aggravated by algorithmic filtering and recommender systems embedded in mobile technology and social media platforms. Yet, genuine innovation thrives on social inclusion fostering a diversity of ideas. To escape these echo chambers, we designed and tested the Skunkworks Finder - an exploratory tool that employs social network analysis to help users discover spaces of difference and otherness in their local urban innovation ecosystem.
Extracted statement — uses Recommendation Method: Algorithm
Research field: Urban Studies and Planning
Title: A Roadmap on Improved Performance-centric Cloud Storage Estimation Approach for Database System Deployment in Cloud Environment
Abstract: Cloud computing has taken the limelight with respect to the present industry scenario due to its multi-tenant and pay-as-you-use models, where users need not bother about buying resources like hardware, software, infrastructure, etc. on an permanently basis. As much as the technological benefits, cloud computing also has its downside. By looking at its financial benefits, customers who cannot afford initial investments, choose cloud by compromising on its concerns, like security, performance, estimation, availability, etc. At the same time due to its risks, customers - relatively majority in number, avoid migration towards cloud. Considering this fact, performance and estimation are being the major critical factors for any application deployment in cloud environment; this paper brings the roadmap for an improved performance-centric cloud storage estimation approach, which is based on balanced PCTFree allocation technique for database systems deployment in cloud environment. Objective of this approach is to highlight the set of key activities that have to be jointly done by the database technical team and business users of the software system in order to perform an accurate analysis to arrive at estimation for sizing of the database. For the evaluation of this approach, an experiment has been performed through varied-size PCTFree allocations on an experimental setup with 100000 data records. The result of this experiment shows the impact of PCTFree configuration on database performance. Basis this fact, we propose an improved performance-centric cloud storage estimation approach in cloud. Further, this paper applies our improved performance-centric storage estimation approach on decision support system (DSS) as a case study.
Extracted statement — Components : Application
Research field: Urban Studies and Planning
Title: A Roadmap on Improved Performance-centric Cloud Storage Estimation Approach for Database System Deployment in Cloud Environment
Abstract: Cloud computing has taken the limelight with respect to the present industry scenario due to its multi-tenant and pay-as-you-use models, where users need not bother about buying resources like hardware, software, infrastructure, etc. on an permanently basis. As much as the technological benefits, cloud computing also has its downside. By looking at its financial benefits, customers who cannot afford initial investments, choose cloud by compromising on its concerns, like security, performance, estimation, availability, etc. At the same time due to its risks, customers - relatively majority in number, avoid migration towards cloud. Considering this fact, performance and estimation are being the major critical factors for any application deployment in cloud environment; this paper brings the roadmap for an improved performance-centric cloud storage estimation approach, which is based on balanced PCTFree allocation technique for database systems deployment in cloud environment. Objective of this approach is to highlight the set of key activities that have to be jointly done by the database technical team and business users of the software system in order to perform an accurate analysis to arrive at estimation for sizing of the database. For the evaluation of this approach, an experiment has been performed through varied-size PCTFree allocations on an experimental setup with 100000 data records. The result of this experiment shows the impact of PCTFree configuration on database performance. Basis this fact, we propose an improved performance-centric cloud storage estimation approach in cloud. Further, this paper applies our improved performance-centric storage estimation approach on decision support system (DSS) as a case study.
Extracted statement — Components : Business