Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Social and Behavioral Sciences
Title: " Does 4-4-2 exist?"– An Analytics Approach to Understand and Classify Football Team Formations in Single Match Situations
Abstract: The chance to win a football match can be significantly increased if the right tactic is chosen and the behavior of the opposite team is well anticipated. For this reason, every professional football club employs a team of game analysts. However, at present game performance analysis is done manually and therefore highly time-consuming. Consequently, automated tools to support the analysis process are required. In this context, one of the main tasks is to summarize team formations by patterns such as 4-4-2 that can give insights into tactical instructions and patterns. In this paper, we introduce an analytics approach that automatically classifies and visualizes the team formation based on the players' position data. We focus on single match situations instead of complete halftimes or matches to provide a more detailed analysis. %in contrast to previous work. The novel classification approach calculates the similarity based on pre-defined templates for different tactical formations. A detailed analysis of individual match situations depending on ball possession and match segment length is provided. For this purpose, a visual summary is utilized that summarizes the team formation in a match segment. An expert annotation study is conducted that demonstrates 1)~the complexity of the task and 2)~the usefulness of the visualization of single situations to understand team formations. The suggested classification approach outperforms existing methods for formation classification. In particular, our approach gives insights into the shortcomings of using patterns like 4-4-2 to describe team formations.
Extracted statement — has research problem: Formation Classification
Research field: Sociology
Title: Telephone psychotherapy and telephone care management for primary care patients starting antidepressant treatment: a randomized controlled trial
Abstract: CONTEXT Both antidepressant medication and structured psychotherapy have been proven efficacious, but less than one third of people with depressive disorders receive effective levels of either treatment. OBJECTIVE To compare usual primary care for depression with 2 intervention programs: telephone care management and telephone care management plus telephone psychotherapy. DESIGN Three-group randomized controlled trial with allocation concealment and blinded outcome assessment conducted between November 2000 and May 2002. SETTING AND PARTICIPANTS A total of 600 patients beginning antidepressant treatment for depression were systematically sampled from 7 group-model primary care clinics; patients already receiving psychotherapy were excluded. INTERVENTIONS Usual primary care; usual care plus a telephone care management program including at least 3 outreach calls, feedback to the treating physician, and care coordination; usual care plus care management integrated with a structured 8-session cognitive-behavioral psychotherapy program delivered by telephone. MAIN OUTCOME MEASURES Blinded telephone interviews at 6 weeks, 3 months, and 6 months assessed depression severity (Hopkins Symptom Checklist Depression Scale and the Patient Health Questionnaire), patient-rated improvement, and satisfaction with treatment. Computerized administrative data examined use of antidepressant medication and outpatient visits. RESULTS Treatment participation rates were 97% for telephone care management and 93% for telephone care management plus psychotherapy. Compared with usual care, the telephone psychotherapy intervention led to lower mean Hopkins Symptom Checklist Depression Scale depression scores (P =.02), a higher proportion of patients reporting that depression was "much improved" (80% vs 55%, P<.001), and a higher proportion of patients "very satisfied" with depression treatment (59% vs 29%, P<.001). The telephone care management program had smaller effects on patient-rated improvement (66% vs 55%, P =.04) and satisfaction (47% vs 29%, P =.001); effects on mean depression scores were not statistically significant. CONCLUSIONS For primary care patients beginning antidepressant treatment, a telephone program integrating care management and structured cognitive-behavioral psychotherapy can significantly improve satisfaction and clinical outcomes. These findings suggest a new public health model of psychotherapy for depression including active outreach and vigorous efforts to improve access to and motivation for treatment.
Extracted statement — has research problem: Psychotherapy for Depression
Research field: Software Engineering
Title: MODELING SAFEST AND OPTIMAL EMERGENCY EVACUATION PLAN FOR LARGE-SCALE PEDESTRIANS ENVIRONMENTS
Abstract: Large-scale events are always vulnerable to natural disasters and man-made chaos which poses great threat to crowd safety. Such events need an appropriate evacuation plan to alleviate the risk of causalities. We propose a modeling framework for large-scale evacuation of pedestrians during emergency situation. Proposed framework presents optimal and safest path evacuation for a hypothetical large-scale crowd scenario. The main aim is to provide the safest and nearest evacuation path because during disastrous situations there is possibility of exit gate blockade and directions of evacuees may have to be changed at run time. For this purpose run time diversions are given to evacuees to ensure their quick and safest exit. In this work, different evacuation algorithms are implemented and compared to determine the optimal solution in terms of evacuation time and crowd safety. The recommended framework incorporates Anylogic simulation environment to design complex spatial environment for large-scale pedestrians as agents.
Extracted statement — has research problem: crowd safety
Research field: Software Engineering
Title: Software Architecture Optimization Methods: A Systematic Literature Review
Abstract: Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.
Extracted statement — has research problem: Software architecture optimization
Research field: Systems and Integrative Physiology
Title: Pilot Study to Estimate "Difficult" Area in e-Learning Material by Physiological Measurements
Abstract: To improve designs of e-learning materials, it is necessary to know which word or figure a learner felt "difficult" in the materials. In this pilot study, we measured electroencephalography (EEG) and eye gaze data of learners and analyzed to estimate which area they had difficulty to learn. The developed system realized simultaneous measurements of physiological data and subjective evaluations during learning. Using this system, we observed specific EEG activity in difficult pages. Integrating of eye gaze and EEG measurements raised a possibility to determine where a learner felt "difficult" in a page of learning materials. From these results, we could suggest that the multimodal measurements of EEG and eye gaze would lead to effective improvement of learning materials. For future study, more data collection using various materials and learners with different backgrounds is necessary. This study could lead to establishing a method to improve e-learning materials based on learners' mental states.
Extracted statement — has research problem: Establishing a method to improve e-learning materials based on learners' mental states.
Research field: Systems Biology
Title: MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context
Abstract: Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.
Extracted statement — has research problem: Visualization
Research field: Theory, Knowledge and Science
Title: Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review
Abstract: Knowledge graphs in manufacturing and production aim to make production lines more efficient and flexible with higher quality output. This makes knowledge graphs attractive for companies to reach Industry 4.0 goals. However, existing research in the field is quite preliminary, and more research effort on analyzing how knowledge graphs can be applied in the field of manufacturing and production is needed. Therefore, we have conducted a systematic literature review as an attempt to characterize the state-of-the-art in this field, i.e., by identifying existing research and by identifying gaps and opportunities for further research. We have focused on finding the primary studies in the existing literature, which were classified and analyzed according to four criteria: bibliometric key facts, research type facets, knowledge graph characteristics, and application scenarios. Besides, an evaluation of the primary studies has also been carried out to gain deeper insights in terms of methodology, empirical evidence, and relevance. As a result, we can offer a complete picture of the domain, which includes such interesting aspects as the fact that knowledge fusion is currently the main use case for knowledge graphs, that empirical research and industrial application are still missing to a large extent, that graph embeddings are not fully exploited, and that technical literature is fast-growing but still seems to be far from its peak.
Extracted statement — has research problem:  finding the primary studies in the existing literature
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 research problem: knowledge graph refinement approaches
Research field: Theory, Knowledge and Science
Title: Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey
Abstract: Graphs arise naturally in many real-world applications including social networks, recommender systems, ontologies, biology, and computational finance. Traditionally, machine learning models for graphs have been mostly designed for static graphs. However, many applications involve evolving graphs. This introduces important challenges for learning and inference since nodes, attributes, and edges change over time. In this survey, we review the recent advances in representation learning for dynamic graphs, including dynamic knowledge graphs. We describe existing models from an encoder-decoder perspective, categorize these encoders and decoders based on the techniques they employ, and analyze the approaches in each category. We also review several prominent applications and widely used datasets, and highlight directions for future research.
Extracted statement — has research problem: review the recent advances in representation learning for dynamic graphs
Research field: Theory, Knowledge and Science
Title: A Survey on Knowledge Graph Embedding: Approaches, Applications and Benchmarks
Abstract: <jats:p>A knowledge graph (KG), also known as a knowledge base, is a particular kind of network structure in which the node indicates entity and the edge represent relation. However, with the explosion of network volume, the problem of data sparsity that causes large-scale KG systems to calculate and manage difficultly has become more significant. For alleviating the issue, knowledge graph embedding is proposed to embed entities and relations in a KG to a low-, dense and continuous feature space, and endow the yield model with abilities of knowledge inference and fusion. In recent years, many researchers have poured much attention in this approach, and we will systematically introduce the existing state-of-the-art approaches and a variety of applications that benefit from these methods in this paper. In addition, we discuss future prospects for the development of techniques and application trends. Specifically, we first introduce the embedding models that only leverage the information of observed triplets in the KG. We illustrate the overall framework and specific idea and compare the advantages and disadvantages of such approaches. Next, we introduce the advanced models that utilize additional semantic information to improve the performance of the original methods. We divide the additional information into two categories, including textual descriptions and relation paths. The extension approaches in each category are described, following the same classification criteria as those defined for the triplet fact-based models. We then describe two experiments for comparing the performance of listed methods and mention some broader domain tasks such as question answering, recommender systems, and so forth. Finally, we collect several hurdles that need to be overcome and provide a few future research directions for knowledge graph embedding.</jats:p>
Extracted statement — has research problem: systematically introduce the existing state-of-the-art approaches and a variety of applications
Research field: Theory, Knowledge and Science
Title: Virtual Knowledge Graphs: An Overview of Systems and Use Cases.
Abstract: In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge. We explain the main notions of this paradigm, its tooling ecosystem and significant use cases in a wide range of applications. Finally, we discuss future research directions.
Extracted statement — has research problem: virtual knowledge graph (VKG) paradigm for data integration
Research field: Theory/Algorithms
Title: Time Series Data Cleaning: A Survey
Abstract: Errors are prevalent in time series data, which is particularly common in the industrial field. Data with errors could not be stored in the database, which results in the loss of data assets. At present, to deal with these time series containing errors, besides keeping original erroneous data, discarding erroneous data and manually checking erroneous data, we can also use the cleaning algorithm widely used in the database to automatically clean the time series data. This survey provides a classification of time series data cleaning techniques and comprehensively reviews the state-of-the-art methods of each type. Besides we summarize data cleaning tools, systems and evaluation criteria from research and industry. Finally, we highlight possible directions time series data cleaning.
Extracted statement — has research problem: Time Series Data Cleaning
Research field: Urban Studies
Title: ISO-Standardized Smart City Platform Architecture and Dashboard
Abstract: A concept guided by the ISO 37120 standard for city services and quality of life is suggested as unified framework for smart city dashboards. The slow (annual, quarterly, or monthly) ISO 37120 indicators are enhanced and complemented with more detailed and person-centric indicators that can further accelerate the transition toward smart cities. The architecture supports three tasks: acquire and manage data from heterogeneous sensors; process data originated from heterogeneous sources (sensors, OpenData, social data, blogs, news, and so on); and implement such collection and processing on the cloud. A prototype application based on the proposed architecture concept is developed for the city of Skopje, Macedonia. This article is part of a special issue on smart cities.
Extracted statement — has research problem: City dashboards
Research field: Urban Studies
Title: Cities-Board: A Framework to Automate the Development of Smart Cities Dashboards
Abstract: Smart cities’ authorities use graphic dashboards to visualize and analyze important information on cities, citizens, institutions, and their interactions. This information supports various decision-making processes that affect citizens’ quality of life. Cities across the world have similar, if not the same, functional and nonfunctional requirements to develop their dashboards. Software developers will face the same challenges and they are likely to provide similar solutions for each developed city dashboard. Moreover, the development of these dashboards implies a significant investment in terms of human and financial resources from cities. The automation of the development of smart cities dashboards is feasible as these visualization systems will have common requirements between cities. This article introduces cities-board, a framework to automate the development of smart cities dashboards based on model-driven engineering. Cities-board proposes a graphic domain-specific language (DSL) that allows the creation of dashboard models with concepts that are closer to city authorities. Cities-board transforms these dashboards models to functional code artifacts by using model-to-model (M2M) and model-to-text (M2T) transformations. We evaluate cities-board by measuring the generation time, and the quality of the generated code under different models configurations. Results show the strengths and weaknesses of cities-board compared against a generic code generation tool.
Extracted statement — has research problem: Model-driven engineering
Research field: Urban Studies
Title: Research Notes: Smart City Control Room Dashboards: Big Data Infrastructure, from data to decision support
Abstract: Smart City Control Rooms are mainly focused on Dashboards which are in turn created by using the socalled Dashboard Builders tools or generated custom. For a city the production of Dashboards is not something that is performed once forever, and it is a continuous working task for improving city monitoring, to follow extraordinary events and/or activities, to monitor critical conditions and cases. Thus, relevant complexities are due to the data aggregation architecture and to the identification of modalities to present data and their identification, prediction, etc., to arrive at producing high level representations that can be used by decision makers. In this paper, the architecture of a Dashboard Builder for creating Smart City Control Rooms is presented. As a validation and test, it has been adopted for generating the dashboards in Florence city and other cities in Tuscany area. The solution proposed has been developed in the context of REPLICATE H2020 European Commission Flagship project on Smart City and Communities.
Extracted statement — has research problem: Smart city control rooms
Research field: Urban Studies
Title: ISO-Standardized Smart City Platform Architecture and Dashboard
Abstract: A concept guided by the ISO 37120 standard for city services and quality of life is suggested as unified framework for smart city dashboards. The slow (annual, quarterly, or monthly) ISO 37120 indicators are enhanced and complemented with more detailed and person-centric indicators that can further accelerate the transition toward smart cities. The architecture supports three tasks: acquire and manage data from heterogeneous sensors; process data originated from heterogeneous sources (sensors, OpenData, social data, blogs, news, and so on); and implement such collection and processing on the cloud. A prototype application based on the proposed architecture concept is developed for the city of Skopje, Macedonia. This article is part of a special issue on smart cities.
Extracted statement — has research problem: Standard for city services
Research field: Urban Studies and Planning
Title: Digital twins technolgy and its data fusion in iron and steel product life cycle
Abstract: The related models in iron and steel product life cycle (IS-PLC), from order, design, purchase, scheduling to specific manufacturing processes (i.e., coking, sintering, blast furnace iron-making, converter, steel-making, continuous steel casting, rolling) is characterized by large-scale, multi-objective, multi-physics, dynamic uncertainty and complicated constraint. To achieve complex task in IS-PLC, involved models need be interrelated and interact, but how to build digital twin models in each IS-PLC stage, and carry out fusion between models and data to achieve virtual space (VS) and physical space (PS) intercorrelation, is a key technology in IS-PLC. In this paper, digital twins modeling and its fusion data problem in each IS-PLC stage are preliminary discussed.
Extracted statement — has research problem: digital twin
Research field: Urban Studies and Planning
Title: Equipment energy consumption management in digital twin shop-floor: A framework and potential applications
Abstract: With increasing attentions focused on the energy consumption (EC) in manufacturing, it is imperative to realize the equipment energy consumption management (EECM) to reduce the EC and improve the energy efficiency. Recently, with the developments of digital twin (DT) and digital twin shop-floor (DTS), the data and models are enriched greatly and a physical-virtual convergence environment is provided. Accordingly, the new chances emerge for improving the EECM in EC monitoring, analysis and optimization. In this situation, the paper proposes the framework of EECM in DTS and discusses the potential applications, aiming at studying the improvements and providing a guideline for the future works.
Extracted statement — has research problem: digital twin