Related papers: An Aspect-Oriented Approach for SaaS Application C…
This paper proposes a new multiple access technique based on the millimeter wave lens-based reconfigurable antenna systems. In particular, to support a large number of groups of users with different angles of departures (AoDs), we integrate…
Aspect based sentiment analysis (ABSA) can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in text. We summarize previous approaches…
Software as a Service (SaaS) is well established as an effective model for the development, deployment and customization of software. As it continues to gain more momentum in the IT industry, many user experience challenges and issues are…
The SaaS paradigm has popularized the usage of pricings, allowing providers to offer customers a wide range of subscription possibilities. This creates a vast configuration space for users, enabling them to choose the features and support…
Aspect-based sentiment analysis (ABSA) aims at extracting opinionated aspect terms in review texts and determining their sentiment polarities, which is widely studied in both academia and industry. As a fine-grained classification task, the…
Aspect-based recommendation methods extract aspect terms from reviews, such as price, to model fine-grained user preferences on items, making them a critical approach in personalized recommender systems. Existing methods utilize graphs to…
Aspect oriented programming aims at achieving better modularization for a system's crosscutting concerns in order to improve its key quality attributes, such as evolvability and reusability. Consequently, the adoption of aspect-oriented…
Current Serverless abstractions (e.g., FaaS) poorly support non-functional requirements (e.g., QoS and constraints), are provider-dependent, and are incompatible with other cloud abstractions (e.g., databases). As a result, application…
We introduce TAPAS (Task-based Adaptation and Planning using AgentS), a multi-agent framework that integrates Large Language Models (LLMs) with symbolic planning to solve complex tasks without the need for manually defined environment…
Cloud computing has fundamentally transformed application development, yet a gap remains between the serverless promise of simplified deployment and its practical realization due to fragmentation across function runtimes, state management,…
The function-as-a-service (FaaS) paradigm is envisioned as the next generation of cloud computing systems that mitigate the burden for cloud-native application developers by abstracting them from cloud resource management. However, it does…
Semantic representation is a key enabler for several application domains, and the multi-agent systems realm makes no exception. Among the methods for semantically representing agents, one has been essentially achieved by taking a…
Metaverse as-a-Service (MaaS) enables Metaverse tenants to execute their APPlications (MetaAPP) by allocating Metaverse resources in the form of Metaverse service functions (MSF). Usually, each MSF is deployed in a virtual machine (VM) for…
Mobility-as-a-Service (MaaS) is a paradigm that encourages the shift from private cars to more sustainable alternative mobility services. MaaS provides services that enhances and enables multiple modes of transport to operate seamlessly and…
Service-oriented computing (SOC) is an interdisciplinary paradigm that revolutionizes the very fabric of distributed software development applications that adopt service-oriented architectures (SOA) can evolve during their lifespan and…
Aspect-Term Sentiment Analysis (ATSA) in multi-aspect sentences faces a fundamental tradeoff between efficiency and expressiveness. Existing models either re-encode the sentence for each aspect or rely on static use of deep representations,…
Modelling and Simulation as a Service (MSaaS) is a promising approach to deploy and execute Modelling and Simulation (M&S) applications quickly and on-demand. An appropriate software architecture is essential to deliver quality M&S…
In this paper, we introduce a new framework called the sentiment-aspect attribution module (SAAM). SAAM works on top of traditional neural networks and is designed to address the problem of multi-aspect sentiment classification and…
Big data analytics (BDA) applications use machine learning algorithms to extract valuable insights from large, fast, and heterogeneous data sources. New software engineering challenges for BDA applications include ensuring performance…
The estimation and improvement of quality attributes in software architectures is a challenging and time-consuming activity. On modern software applications, a model-based representation is crucial to face the complexity of such activity.…