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The rise of social networks for software development has attached a notion of popularity to open source projects. This work attempts to extract knowledge from the differences between popular and unpopular Python projects on GitHub. A large set of projects was mined for a rich variety of features that measure language utilization, documentation, and code volume. These features were used to train a...
Twitter user profile information is very useful for various fields such as marketing, HRD, advertising, and personalization. Since user profile provided by Twitter is very limited, some latent attributes such as gender, age, work, or interest should be predicted. In this paper, we aim to predict those four latent attributes using her/his tweet and bio data by employing machine learning techniques...
The autism spectrum disorder (ASD) is increasingly being recognized as a major public health issue which affects approximately 0.5–0.6% of the population. Promoting the general awareness of the disorder, increasing the engagement with the affected individuals and their carers, and understanding the success of penetration of the current clinical recommendations in the target communities, is crucial...
Detecting clusters in the encounter graphs generated from reality mining data is one way of detecting the social and spatial relationships of participants. However, many of the existing clustering algorithms do not factor in the time since encounters, and can only be used to describe a single aggregated snapshot of the data. This paper describes a spatio-temporal clustering technique which has been...
The RAISE'13 workshop brought together researchers from the AI and software engineering disciplines to build on the interdisciplinary synergies which exist and to stimulate research across these disciplines. The first part of the workshop was devoted to current results and consisted of presentations and discussion of the state of the art. This was followed by a second part which looked over the horizon...
The Mining Software Repositories community typically focuses on data from software configuration management tools, mailing lists, and bug tracking repositories to uncover interesting and actionable information about the evolution of software systems. However, the techniques employed and the challenges faced when mining are not restricted to these types of repositories. In this paper, we present an...
In this paper, we propose a unified framework OCTracker for tracking overlapping community evolution in online social networks. OCTracker adapts a preliminary community structure towards dynamic changes in social networks using a novel density-based approach for detecting overlapping community structures and automatically detects evolutionary events like birth, growth, contraction, merge, split, and...
There may be several reasons why people publish together. Above all, the fact that the authors share common professional interests is the main reason. In our research we work with the DBLP dataset which contains the basic bibliographic information of publications from the computer science field. These data are freely available and contain highly relevant information about publication activity from...
New technologies allow to store vast amount of data about users interaction. From those data the social network can be created. Additionally, because usually also time and dates of this activities are stored, the dynamic of such network can be analyzed by splitting it into many timeframes representing the state of the network during specific period of time. One of the most interesting issue is group...
We provide an overview of the current data management research issues in the context of the Semantic Web. The objective is to introduce the audience into the area of the Semantic Web, and to highlight the fact that the area provides many interesting research opportunities for the data management community. A new model, the Resource Description Framework (RDF), coupled with a new query language, called...
Traditional clustering algorithms identify just a single clustering of the data. Today's complex data, however, allow multiple interpretations leading to several valid groupings hidden in different views of the database. Each of these multiple clustering solutions is valuable and interesting as different perspectives on the same data and several meaningful groupings for each object are given. Especially...
While ICDM has traditionally enjoyed an unusually high quality of reviewing, there is no doubt that publishing in ICDM is very challenging. In this tutorial Dr. Keogh will demonstrate some simple ideas to enhance the probability of success in getting your paper published in a top data mining conference, and after the work is published, getting it highly cited.
In software development, the knowledge of developers, architects and end users is spread out across dozens of development artifacts. Historically, structured development artifacts such as source code have been the primary focus of software engineering research, but the last couple of years have seen a dramatic increase of research on unstructured data, such as free-form text requirements and specifications,...
We examine digital social media ecosystems such as blogs and mailing lists from the perspective of communities of practice. We observe behaviors of agents and specify prevalent patterns of collaborations in digital media ecosystem.We describe several techniques important in patterns specification such as social network analysis and content analysis. The conceptualization of our observations was done...
It has become difficult to discover quality content within forums websites due to the increasing amount of User Generated Content (UGC) on the Web. Many existing websites have relied on their users to explicitly rate content quality. The main problem with this approach is that the majority of content often receives insufficient rating. Current automated content rating solutions have evaluated linguistic...
A bibliographic database houses vital information pertinent to the research community. By extracting implicit hidden information in such data collections, social networks can be used to represent the various data inter-relationships.In this paper, we propose a new method for the discovery and visualization of research communities from bibliography information. We utilize the hierarchical overlapping...
This paper presents project 'Alfalab'. Alfalab is a collaborative frame work project of the Royal Netherlands Academy of Arts and Sciences (KNAW). It explores the success and fail factors for virtual research collaboration and supporting digital infrastructure in the Humanities. It does so by delivering a virtual research environment engineered through a virtual R&D collaborative and by drawing...
In the context of socio-economic and cultural diversity of continental proportions lived by Brazilian citizens, the e-Cidadania project aims at the development of systems for the constitution of a digital culture among those that are not familiar with technology. One of the project's main contributions is the Inclusive Social Network (ISN) Vila na Rede, which is being constructed based on methods...
The Engineering Leadership Program is entering its fourth year as a co-curricular program at Iowa State University. It is a values-based learning community for engineering students passionate about contributing to their communities, locally or globally. As the program has grown from 15 to over 80 scholars, it has experienced creative challenges such as retaining a sense of community, succession planning,...
There is agreement on the need for change in engineering education, but lacking are the motivation, knowledge, or skills to effect change. With that in mind, we held a workshop in June 2009 that sought to engage faculty members who are change leaders. Over the two-day workshop, we solicited their views on departmental and institutional challenges, the knowledge, skills and abilities (KSAs) necessary...
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