Process mining encompasses a series of tasks aimed at discovering knowledge about business processes from event logs underlying information systems deployed in organizations. Considering real-world business processes, high-complexity issues often prevent process mining techniques from producing satisfactory results. Business processes’ complexity arises from: (i) high behavioral variability as presented in unstructured processes, e.g. knowledge intensive processes, in which decisions commonly dependent on human actions; (ii) data volume, as it can reach big data levels in organizations with high-volume operations. Trace clustering can support mitigating high-complexity related issues. The process instance profiles resulting from trace clustering divide a complex problem into smaller and simpler ones. However, interpreting clustering results frequently requires decision-making and reasoning that might benefit from domain experts’ knowledge. Especially, in trace clustering-based process mining tasks, domain experts involvement enable results evaluation from the business process perspective. In this paper, a proposal for a trace clustering results visualization is presented. This visualization strategy supports evaluation from a business process perspective, enabling human-in-the-loop strategies. In order to illustrate the usefulness and appropriateness of the visualization, we present three use cases modeled on real-world event logs.

In recent years, machine learning has been used for data processing and analysis, providing insights to businesses and policymakers. Deep learning technology is promising to further revolutionize this processing leading to better and more accurate results. Current trends in information and communication technology are accelerating widespread use of web services in supporting a service-oriented architecture (SOA) consisting of services, their compositions, interactions, and management. Deep learning approaches can be applied to support the development of SOA-based solutions, leveraging the vast amount of data on web services currently available. On the other hand, SOA has mechanisms that can support the development of distributed, flexible, and reusable infrastructures for the use of deep learning. This paper presents a literature survey and discusses how SOA can be enabled by as well as facilitate the use of deep learning approaches in different types of environments for different levels of users.

The concept of children's toys has undergone many changes over the years, evolving from simple physical products to toys that add elements of the digital world using software and hardware components. This evolution has raised concerns about potential child privacy issues regarding the use of smart toys. A smart toy consists of a physical component connected to a computer system with online services to enhance the functionality of a traditional toy. This type of toy is still not widely known in Brazil and hence the opinion of Brazilian consumers regarding the acceptance of this technology when it is widespread in this country is not known yet. This paper aims to present the results of an evaluation about the perception of potential Brazilian consumers about issues involving children's privacy with the use of smart toys and whether this technology would be accepted when available in the Brazilian toy market. Semi-structured interviews were conducted with 14 participants producing data that were analyzed through the content analysis technique. The results showed concern on the part of parents when their children are connected to the internet. Moreover, parental control in smart toys would be well accepted by these potential consumers.

Techniques of functional size measurement are easily found in the literature, however, in the evaluation process of these techniques is not always approached which makes its validity questionable. The evaluation of the Business Process Point Analysis (BPPA) technique is the object of study of this article that aims to consistently evaluate its reproducibility and accuracy, identifying its limitations. BPPA was proposed so that project managers can systematically estimate the functional size of a business process automation project. Thus, this article presents the execution of a quasi-experiment realized with 58 graduate and postgraduate students, who measured the functional size of three business process models. The results of this experiment present the low reproducibility and accuracy of the technique as well as its limitations.

The large amount of information in electronic contracts hampers their establishment due to high complexity. An approach inspired in software product line and based on feature modeling was proposed to make this process more systematic through information reuse and structuring. To allow the coverage assessment of this and other similar approaches, this paper presents a set of requirements that should be met by an approach in order to obtain success in supporting the process of Web services negotiation and contracting. By assessing the feature-based approach in relation to the proposed requirements, it was showed that the approach does not allow the price of services and of quality of services (QoS) attributes to be considered in the negotiation and included in the electronic contract. Thus, this paper also presents an extension of such approach in which prices and price types associated to Web services and QoS levels are applied. An extended toolkit prototype is also presented as well as an experimentation example of the proposed approach.

Electronic contracts describe inter-organizational business processes in terms of supply and consumption of electronic services (commonly Web services). The establishment of e-contracts in a particular business domain usually involves a set of well-defined common and variable properties. These properties are not fully exploited by the existing e-contract establishment approaches. Feature modeling is a software engineering technique that has been widely used for capturing and managing commonalities and variabilities of product families in the context of software product line. This paper presents a feature-based approach to support Web services e-contract (WS-contract) establishment. The approach aims at improving the information structure and reuse of WS-contracts, including the QoS attributes. Features are used to represent possible WS-contract elements in order to drive WS-contract template instantiation, thus acting as a configuration space manager. A toolkit named FeatureContract was developed to automatically support the proposed approach. A case study was carried out within the telecom context to show the approach feasibility.