Skill ranking of researchers via hypergraph

Researchers use various skills in their works, such as writing, data analysis and experiments design. These research skills have greatly influenced the quality of their research outputs, as well as their scientific impact. Although many indicators have been proposed to quantify the impact of researchers, studies of evaluating their scientific research skills are very rare. In this paper, we analyze the factors affecting researchers’ skill ranking and propose a new model based on hypergraph theory to evaluate the scientific research skills. To validate our skill ranking model, we perform experiments on the PLOS ONE dataset and compare the rank of researchers’ skills with their papers’ citation counts and h-index. Finally, we analyze the patterns about how researchers’ skill ranking increased over time. Our studies also show the change patterns of researchers between different skills

SCSMiner: mining social coding sites for software developer recommendation with relevance propagation

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. With the advent of social coding sites, software development has entered a new era of collaborative work. Social coding sites (e.g., GitHub) can integrate social networking and distributed version control in a unified platform to facilitate collaborative developments over the world. One unique characteristic of such sites is that the past development experiences of developers provided on the sites convey the implicit metrics of developer’s programming capability and expertise, which can be applied in many areas, such as software developer recruitment for IT corporations. Motivated by this intuition, we aim to develop a framework to effectively locate the developers with right coding skills. To achieve this goal, we devise a generativ e probabilistic expert ranking model upon which a consistency among projects is incorporated as graph regularization to enhance the expert ranking and a perspective of relevance propagation illustration is introduced. For evaluation, StackOverflow is leveraged to complement the ground truth of expert. Finally, a prototype system, SCSMiner, which provides expert search service based on a real-world dataset crawled from GitHub is implemented and demonstrated

Language Advice Networks: a form of social capital in the multinational corporation

This thesis introduces the emerging phenomenon of Language Advice Networks (LANs) in multilingual, multinational corporations. As an informal network of individuals, a LAN is utilized on a need basis to seek and offer language-related advice, with the common goal of performing efficiently and avoiding more time-consuming traditional translation. Through three separate yet related studies, I introduce the LAN, its structural and relational formation, and the career implications of LAN engagement for individuals. The three studies entail both qualitative and quantitative approaches. Conducted in QatarCo (a pseudonym), the MNC’s headquarters is located in Qatar and operates with English as its lingua franca. I accumulated participant observation fieldnotes for 10 consecutive months, conducted 65 one-to-one, semistructured interviews and two focus groups, and surveyed 107 employees representing four departments. Study 1 explores how employees with varying degrees of lingua franca fluency deploy their intra-firm social capital to exchange – seek and offer – language-related knowledge, on a need basis. Using a mixed methods approach, I define the LAN, elaborate its properties and dimensions, and distinguish its structure from that of general advice networks. Study 2 extends the structural exposition by examining the relational dimension of LANs. To investigate the individual and dyadic attributes of the language advisors. I apply exponential random graph modelling to reveal that that the advisory role is predicted by a cosmopolitan mindset: ability to articulate advice in a manner understood by a culturally dissimilar counterpart. Study 3 uses grounded theory to demonstrate that advising in a LAN entails generalized reciprocity with career implications, including enhanced status, non-financial rewards, financial incentives, and sense of empowerment. The data also indicate that the relationship between LAN engagement and career success can be explained through two mechanisms: establishing a rewarding reputation and enhancing one’s intra-firm social capital. I conclude by discussing the thesis’s theoretical contributions to the International Business, career, and social capital literature, as well as managerial implications, research limitations, and future research directions

Engineering Design Team Leadership in Undergraduate Design Teams

The objective of this research is to develop an understanding of the emergence and distribution of leadership behaviors in engineering design teams. This research was conducted with undergraduate engineering students and explored leadership behaviors within design teams in a variety of contexts. Undergraduates were selected for the study since they possessed similar education and skills as a novice engineer in industry. A mixed methods approach incorporated qualitative and quantitative techniques including interview, case study, and protocol study instruments. The use of these methods enabled the exploration of leadership in both natural and controlled environments to capitalize on the research advantages of each. Interviews were employed to understand faculty perceptions of leadership in design teams. The case study enabled the identification of leadership in a natural context without the need to control the multitude of variables in collaborative design. The protocol study provided a more focused and controlled study to identify patterns of leadership emergence and distribution of functions within a specific conceptual design activity: function modeling. The teams examined ranged from three to four-member design teams in the protocol study to ten-member teams with behavior resembling multiteam systems in the case studies. The resulting insights provide increased understanding of the emergence of leadership and the distribution of leadership functions within design teams. Interviews manifested faculty perceptions that formal structures are developed early and that informal roles emerge throughout projects, with communication skills playing an important role. Faculty perceptions on leadership covered a broad range of leadership functions including “performing task” and “consideration.” The density of leadership networks during case studies confirmed the emergence of informal leadership functions among designers and indicated variations in function distribution at sampling points. Protocol studies indicated that informal leadership was established early, and that leaders active early remained active throughout these focused sessions. A single instance of variation in protocol study team size demonstrated a structural parity in a three-member team that was not observed in four-member teams. This supports faculty perception that larger and multi-dimensional teams also provided different opportunities for leadership development. This understanding will form the basis for further research into leadership of design teams and may assist in the development of leadership interventions in engineering design teams and design education

Algorithms for the Analysis of Spatio-Temporal Data from Team Sports

Modern object tracking systems are able to simultaneously record trajectories—sequences of time-stamped location points—for large numbers of objects with high frequency and accuracy. The availability of trajectory datasets has resulted in a consequent demand for algorithms and tools to extract information from these data. In this thesis, we present several contributions intended to do this, and in particular, to extract information from trajectories tracking football (soccer) players during matches. Football player trajectories have particular properties that both facilitate and present challenges for the algorithmic approaches to information extraction. The key property that we look to exploit is that the movement of the players reveals information about their objectives through cooperative and adversarial coordinated behaviour, and this, in turn, reveals the tactics and strategies employed to achieve the objectives. While the approaches presented here naturally deal with the application-specific properties of football player trajectories, they also apply to other domains where objects are tracked, for example behavioural ecology, traffic and urban planning

Proceedings, MSVSCC 2013

Proceedings of the 7th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 11, 2013 at VMASC in Suffolk, Virginia

Reading the news through its structure: new hybrid connectivity based approaches

In this thesis a solution for the problem of identifying the structure of news published by online newspapers is presented. This problem requires new approaches and algorithms that are capable of dealing with the massive number of online publications in existence (and that will grow in the future). The fact that news documents present a high degree of interconnection makes this an interesting and hard problem to solve. The identification of the structure of the news is accomplished both by descriptive methods that expose the dimensionality of the relations between different news, and by clustering the news into topic groups. To achieve this analysis this integrated whole was studied using different perspectives and approaches. In the identification of news clusters and structure, and after a preparatory data collection phase, where several online newspapers from different parts of the globe were collected, two newspapers were chosen in particular: the Portuguese daily newspaper Público and the British newspaper The Guardian. In the first case, it was shown how information theory (namely variation of information) combined with adaptive networks was able to identify topic clusters in the news published by the Portuguese online newspaper Público. In the second case, the structure of news published by the British newspaper The Guardian is revealed through the construction of time series of news clustered by a kmeans process. After this approach an unsupervised algorithm, that filters out irrelevant news published online by taking into consideration the connectivity of the news labels entered by the journalists, was developed. This novel hybrid technique is based on Qanalysis for the construction of the filtered network followed by a clustering technique to identify the topical clusters. Presently this work uses a modularity optimisation clustering technique but this step is general enough that other hybrid approaches can be used without losing generality. A novel second order swarm intelligence algorithm based on Ant Colony Systems was developed for the travelling salesman problem that is consistently better than the traditional benchmarks. This algorithm is used to construct Hamiltonian paths over the news published using the eccentricity of the different documents as a measure of distance. This approach allows for an easy navigation between published stories that is dependent on the connectivity of the underlying structure. The results presented in this work show the importance of taking topic detection in large corpora as a multitude of relations and connectivities that are not in a static state. They also influence the way of looking at multi-dimensional ensembles, by showing that the inclusion of the high dimension connectivities gives better results to solving a particular problem as was the case in the clustering problem of the news published online.Neste trabalho resolvemos o problema da identificação da estrutura das notícias publicadas em linha por jornais e agências noticiosas. Este problema requer novas abordagens e algoritmos que sejam capazes de lidar com o número crescente de publicações em linha (e que se espera continuam a crescer no futuro). Este facto, juntamente com o elevado grau de interconexão que as notícias apresentam tornam este problema num problema interessante e de difícil resolução. A identificação da estrutura do sistema de notícias foi conseguido quer através da utilização de métodos descritivos que expõem a dimensão das relações existentes entre as diferentes notícias, quer através de algoritmos de agrupamento das mesmas em tópicos. Para atingir este objetivo foi necessário proceder a ao estudo deste sistema complexo sob diferentes perspectivas e abordagens. Após uma fase preparatória do corpo de dados, onde foram recolhidos diversos jornais publicados online optou-se por dois jornais em particular: O Público e o The Guardian. A escolha de jornais em línguas diferentes deve-se à vontade de encontrar estratégias de análise que sejam independentes do conhecimento prévio que se tem sobre estes sistemas. Numa primeira análise é empregada uma abordagem baseada em redes adaptativas e teoria de informação (nomeadamente variação de informação) para identificar tópicos noticiosos que são publicados no jornal português Público. Numa segunda abordagem analisamos a estrutura das notícias publicadas pelo jornal Britânico The Guardian através da construção de séries temporais de notícias. Estas foram seguidamente agrupadas através de um processo de k-means. Para além disso desenvolveuse um algoritmo que permite filtrar de forma não supervisionada notícias irrelevantes que apresentam baixa conectividade às restantes notícias através da utilização de Q-analysis seguida de um processo de clustering. Presentemente este método utiliza otimização de modularidade, mas a técnica é suficientemente geral para que outras abordagens híbridas possam ser utilizadas sem perda de generalidade do método. Desenvolveu-se ainda um novo algoritmo baseado em sistemas de colónias de formigas para solução do problema do caixeiro viajante que consistentemente apresenta resultados melhores que os tradicionais bancos de testes. Este algoritmo foi aplicado na construção de caminhos Hamiltonianos das notícias publicadas utilizando a excentricidade obtida a partir da conectividade do sistema estudado como medida da distância entre notícias. Esta abordagem permitiu construir um sistema de navegação entre as notícias publicadas que é dependente da conectividade observada na estrutura de notícias encontrada. Os resultados apresentados neste trabalho mostram a importância de analisar sistemas complexos na sua multitude de relações e conectividades que não são estáticas e que influenciam a forma como tradicionalmente se olha para sistema multi-dimensionais. Mostra-se que a inclusão desta dimensões extra produzem melhores resultados na resolução do problema de identificar a estrutura subjacente a este problema da publicação de notícias em linha

Insight into kognitive structure : Assessment, analysis, and instructional innovations

Strong theoretical foundations and precise methodology are always the one and only starting point for good research. Without sound foundations nothing follows, and thus a deep understanding of the theoretical assumptions of cognitive structure and methodology involved is mandatory for research on cognition and learning as well as for instructional design. Several research projects contribute to the overall scientific knowledge with regard to cognitive structure and its assessment, analysis, and instruction. Cognitive structure continued to be a key subject in different fields of research for more than a century. For good reason. Foundations from cognitive science, computer science, philosophy, and cognitive psychology describe the workings of the human mind in tasks of deduktive and inductive reasoning, especially for reasoning in uncertainty. They lead to theories of problem solving and to theories of learning and instruction which are both highly interdependent. The development of useful systems has always been a goal for scientists and engineers serving professional communities in the fields of instructional design and instructional systems development. This kumulative work outlines a research project which enables an insight into cognitive structure highlighting ways of assessment, analysis, and instructional innovations