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Soler-Dominguez, Amparo; Juan, Angel A.; Kizys, Renatas
doi: 10.1145/3054133pmid: N/A
Modern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision-making in a number of fields, such as logistics and transportation, telecommunication networks, bioinformatics, finance, and the like. The continuous increase in computing power, together with advancements in metaheuristics frameworks and parallelization strategies, are empowering these types of algorithms as one of the best alternatives to solve rich and real-life combinatorial optimization problems that arise in a number of financial and banking activities. This article reviews some of the works related to the use of metaheuristics in solving both classical and emergent problems in the finance arena. A non-exhaustive list of examples includes rich portfolio optimization, index tracking, enhanced indexation, credit risk, stock investments, financial project scheduling, option pricing, feature selection, bankruptcy and financial distress prediction, and credit risk assessment. This article also discusses some open opportunities for researchers in the field, and forecast the evolution of metaheuristics to include real-life uncertainty conditions into the optimization problems being considered.
Tsvetkova, Milena; Yasseri, Taha; Meyer, Eric T.; Pickering, J. Brian; Engen, Vegard; Walland, Paul; Lüders, Marika; Følstad, Asbjørn; Bravos, George
doi: 10.1145/3039868pmid: N/A
In the current hyperconnected era, modern Information and Communication Technology (ICT) systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly visible and participatory role. Such Human-Machine Networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations. The challenge in designing successful HMNs is that they cannot be developed and implemented in the same manner as networks of machines nodes alone, or following a wholly human-centric view of the network. The problem requires an interdisciplinary approach. Here, we review current research of relevance to HMNs across many disciplines. Extending the previous theoretical concepts of socio-technical systems, actor-network theory, cyber-physical-social systems, and social machines, we concentrate on the interactions among humans and between humans and machines. We identify eight types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. We systematically select literature on each of these types and review it with a focus on implications for designing HMNs. Moreover, we discuss risks associated with HMNs and identify emerging design and development trends.
doi: 10.1145/3047307pmid: N/A
With the rapid development of information storage and networking technologies, quintillion bytes of data are generated every day from social networks, business transactions, sensors, and many other domains. The increasing data volumes impose significant challenges to traditional data analysis tools in storing, processing, and analyzing these extremely large-scale data. For decades, hashing has been one of the most effective tools commonly used to compress data for fast access and analysis, as well as information integrity verification. Hashing techniques have also evolved from simple randomization approaches to advanced adaptive methods considering locality, structure, label information, and data security, for effective hashing. This survey reviews and categorizes existing hashing techniques as a taxonomy, in order to provide a comprehensive view of mainstream hashing techniques for different types of data and applications. The taxonomy also studies the uniqueness of each method and therefore can serve as technique references in understanding the niche of different hashing mechanisms for future development.
doi: 10.1145/3038925pmid: N/A
Hypervideos and interactive multimedia presentations allow the creation of fully interactive and enriched video. It is possible to organize video scenes in a nonlinear way. Additional information can be added to the video ranging from short descriptions to images and more videos. Hypervideos are video-based but also provide navigation between video scenes and additional multimedia elements. Interactive multimedia presentations consist of different media with a temporal and spatial synchronization that can be navigated via hyperlinks. Their creation and description requires description formats, multimedia models, and standardsas well as players. Specialized authoring tools with advanced editing functions allow authors to manage all media files, link and arrange them to an overall presentation, and keep an overview during the whole process. They considerably simplify the creation process compared to writing and editing description documents in simple text editors. Data formats need features that describe interactivity and nonlinear navigation while maintaining temporal and spatial synchronization. Players should be easy to use with extended feature sets keeping elements synchronized. In this article, we analyzed more than 400 papers for relevant work in this field. From the findings we discovered a set of trends and unsolved problems, and propose directions for future research.
Bashroush, Rabih; Garba, Muhammad; Rabiser, Rick; Groher, Iris; Botterweck, Goetz
doi: 10.1145/3034827pmid: N/A
Software product lines (SPL) aim at reducing time-to-market and increasing software quality through extensive, planned reuse of artifacts. An essential activity in SPL is variability management, i.e., defining and managing commonality and variability among member products. Due to the large scale and complexity of today's software-intensive systems, variability management has become increasingly complex to conduct. Accordingly, tool support for variability management has been gathering increasing momentum over the last few years and can be considered a key success factor for developing and maintaining SPLs. While several studies have already been conducted on variability management, none of these analyzed the available tool support in detail. In this work, we report on a survey in which we analyzed 37 existing variability management tools identified using a systematic literature review to understand the tools characteristics, maturity, and the challenges in the field. We conclude that while most studies on variability management tools provide a good motivation and description of the research context and challenges, they often lack empirical data to support their claims and findings. It was also found that quality attributes important for the practical use of tools such as usability, integration, scalability, and performance were out of scope for most studies.
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