Third special issue on knowledge discovery and business intelligence

[Excerpt] Expert Systems were proposed in the mid 1970s (Arnott & Pervan, 2014) with the goal of building computerized systems that mimic human behavior to solve real-world tasks. Such systems were based on artificial intelligence (AI) techniques, typically by adopting explicit (human understandable) knowledge, extracted from domain experts (e.g. by using interviews) and that was stored in a knowledge base (Buchanan, 1986).We would like to thank the other KDBI 2015 track (of EPIA) co-organizers, Luis Cavique, Joao Gama and Nuno Marques. Also, we thank the authors, who contributed with their papers, and the reviewers (from the KDBI 2015 program committee and the ES journal). This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia with in the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

The Emergence of Law Consultants

In this paper we study a slightly subcritical Choquard problem on a bounded domain A. We prove that the number of positive solutions depends on the topology of the domain. In particular when the exponent of the nonlinearity approaches the critical one, we show the existence of cat (A) + 1 solutions. Here cat (A) denotes the Lusternik–Schnirelmann category

Our Very Privileged Executive: Why the Judiciary Can (and Should) Fix the State Secrets Privilege

This paper was first presented at the Temple Law Review Symposium on Executive Power. In Reynolds v. United States, the Supreme Court shaped the state secrets privilege (the Privilege) as one akin to that against self-incrimination. In recent litigation, the government has asserted the Privilege in motions for pre-discovery dismissal, thus transforming the Privilege into a form of executive immunity. This Paper argues that courts must step in to return the Privilege to a scope more in keeping with its status as a form of evidentiary privilege. After reviewing the doctrinal origins of the Privilege, the Paper explores three types of issues implicated by the government\u27s invocation of the Privilege. The government, in calling for judicial deference to executive assertions of the Privilege, often realies on (1) separation of powers arguments or on (2) arguments sounding in institutional competence. Courts are often swayed by such arguments and thus give relatively little consideration to the (3) conflict of interest inherent in the government\u27s assertion of the Privilege and the impact of the successful invocation of the Privilege on the rights of individual litigants. The Paper then proceeds to address arguments that Congress can provide a check on executive abuse of the Privilege. The Paper argues that, assuming that Congress has constitutional authority, it lacks the will or the institutional competence to provide a proper solution to the problems raised by the Privilege. Instead, the Paper contends that, since courts created the Privilege, courts are best positioned to rein it in. The final section of the Paper provides examples drawn from case law illustrating mechanisms whereby courts can protect state secrets while also giving litigants adverse to the government their day in court

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Data Warehouse And Data Mining – Neccessity Or Useless Investment

The organization has optimized databases which are used in current operations and also used as a part of decision support. What is the next step? Data Warehouses and Data Mining are indispensable and inseparable parts for modern organization. Organizations will create data warehouses in order for them to be used by business executives to take important decisions. And as data volume is very large, and a simple filtration of data is not enough in taking decisions, Data Mining techniques will be called on. What must an organization do to implement a Data Warehouse and a Data Mining? Is this investment profitable (especially in the conditions of economic crisis)? In the followings we will try to answer these questions.database, data warehouse, data mining, decision, implementing, investment

Semantic process mining tools: core building blocks

Process mining aims at discovering new knowledge based on information hidden in event logs. Two important enablers for such analysis are powerful process mining techniques and the omnipresence of event logs in today's information systems. Most information systems supporting (structured) business processes (e.g. ERP, CRM, and workflow systems) record events in some form (e.g. transaction logs, audit trails, and database tables). Process mining techniques use event logs for all kinds of analysis, e.g., auditing, performance analysis, process discovery, etc. Although current process mining techniques/tools are quite mature, the analysis they support is somewhat limited because it is purely based on labels in logs. This means that these techniques cannot benefit from the actual semantics behind these labels which could cater for more accurate and robust analysis techniques. Existing analysis techniques are purely syntax oriented, i.e., much time is spent on filtering, translating, interpreting, and modifying event logs given a particular question. This paper presents the core building blocks necessary to enable semantic process mining techniques/tools. Although the approach is highly generic, we focus on a particular process mining technique and show how this technique can be extended and implemented in the ProM framework tool