The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Individuals in society differ ideologically both online and offline. As the nature of discussions and communication evolve, so do the dynamics within collective groups. User participation on issues such as political discourse affect the opinions of collective groups prior to, during, and after the occurrence of significant events. Changes in engagement can be influenced by choice in words during these...
The 15th edition of the "Adaptive Computing (and Agents) for Enhanced Collaboration" track at WETICE 2017 focuses on the areas of adaptive agent-based services and adaptive techniques for enterprises. The purpose of the track is to bring together researches in the fields of software agents and adaptive computing as they relate to the context of adaptive techniques and enterprise collaboration...
Crowdsourcing labor market platforms consist of a variety of jobs spanning multiple problem domains and their respective specialized or diverse worker pools. Each platform currently operates independently and isolated from the potential benefits of sharing job and worker pool data across platforms. Previous work introduces infrastructure that optimizes the sharing of both job and worker data collectively,...
Elastic systems utilize both human and machine working units to accomplish tasks that are eligible for crowdsourcing. The quality in the results of work completed by either type of computing unit is tantamount on the characteristics they bear. In this paper we draw parallels from our previous work into looking at the suitability of working units in completing viable tasks in crowdsourcing. We seek...
While the crowd sourcing paradigm facilitates the use of human-enacted resources from large groups of individuals, matching workers with jobs is limited by the need for these potential workers to proactively subscribe to various networks. This subscription phase is part of an "open call model" that reduces the ability for crowd sourcing platforms to scale or retain crowd-oriented workers...
Generally, in crowdsourcing, providers advertise their task offerings (i.e. the open call model) largely to crowdworkers who subscribe their interest in working (i.e. subscription model). The combined open call and subscription model represent significant bottlenecks for recruitment in the paradigm of crowdsourcing. Consequently, attracting and retaining a crowd are the major challenges to the success...
When leveraging the crowd to perform complex tasks, it is imperative to identify the most effective worker for a particular job. Demographic profiles provided by workers, skill self-assessments by workers, and past performance as captured by employers all represent viable data points available within labor markets. Employers often question the validity of a worker's self-assessment of skills and expertise...
Crowd sourcing is a paradigm where activities are outsourced to human actors (i.e. The crowd) with the aim of discovering and evaluating solutions. This paradigm can also be extended to develop a collective intelligence of large-scale crowd communities that when combined with traditional computing resources can derive solutions that neither humans nor machines can solve alone. Such hybrid systems,...
Increasing popularity in the use of crowd sourcing has led to many tasks that can be fulfilled by the wisdom of human actors. When natural disasters or criminal activities occur, then sometimes crowd sourced tasks must be generated in real-time and must be fulfilled in an on-demand fashion. Effective use of crowd sourcing techniques requires an array of services that fulfil many dimensions of the...
Crowd computing leverages human input in order to execute tasks that are computationally expensive, due to complexity and/or scale. Combined with automation, crowd computing can help solve problems efficiently and effectively. In this work, we introduce an elasticity framework that adaptively optimizes the use of human and automated software resources in order to maximize overall performance. This...
Despite the plethora of polls, surveys, and reports stating that most companies are embracing Big Data, there is slow adoption of Big Data technologies, like Hadoop, in enterprises. One of the primary reasons for this is that companies have significant investments in legacy languages and systems and the process of migrating tone wer (Big Data) technologies would represent a substantial commitment...
Crowdsourcing enables one to leverage the power of the crowd. Normally, it involves utilizing humans for tasks that machines have difficulty performing. We propose a system, delivered as a mobile service, which dynamically adapts to the application domain and selects a combination of human and machine crowdsourcing components. Our work is towards the design of elastic systems that adaptively optimizes...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.