Fourth special issue on knowledge discovery and business intelligence

[Excerpt] Expert Systems (ES) are a core element of human decision making. Initially, in the 70s and 80s, ES were focused on extracting explicit knowledge from human experts. With the availability of big data, after the 2000s, ES incorporated data-driven models, thus being associated with business intelligence, big data, data science and machine learning systems [Cortez and Santos, 2017]. The importance of data-driven models in the ES area is confirmed by the recent Wiley’s Expert Systems (EXSY) literature survey that analyzed all journal research articles published from 2000 to 2016 [Cortez et al., 2018]. The survey revealed data-driven as the most prevalent ES method type, corresponding to around 35% of all recently published EXSY papers. [...]We would like to thank the other KDBI 2017 track (of EPIA) co-organizers: Albert Bifet, Luis Cavique, and Nuno Marques. Also, we thank the authors, who contributed with their papers, and the reviewers (from the KDBI 2017 program committee and the EXSY journal). This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

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

Information Outlook, September 2005

Volume 9, Issue 9https://scholarworks.sjsu.edu/sla_io_2005/1008/thumbnail.jp

Formally analysing the concepts of domestic violence.

The types of police inquiries performed these days are incredibly diverse. Often data processing architectures are not suited to cope with this diversity since most of the case data is still stored as unstructured text. In this paper Formal Concept Analysis (FCA) is showcased for its exploratory data analysis capabilities in discovering domestic violence intelligence from a dataset of unstructured police reports filed with the regional police Amsterdam-Amstelland in the Netherlands. From this data analysis it is shown that FCA can be a powerful instrument to operationally improve policing practice. For one, it is shown that the definition of domestic violence employed by the police is not always as clear as it should be, making it hard to use it effectively for classification purposes. In addition, this paper presents newly discovered knowledge for automatically classifying certain cases as either domestic or non-domestic violence is. Moreover, it provides practical advice for detecting incorrect classifications performed by police officers. A final aspect to be discussed is the problems encountered because of the sometimes unstructured way of working of police officers. The added value of this paper resides in both using FCA for exploratory data analysis, as well as with the application of FCA for the detection of domestic violence.Formal concept analysis (FCA); Domestic violence; Knowledge discovery in databases; Text mining; Exploratory data analysis; Knowledge enrichment; Concept discovery;

Enhancing simulation education with intelligent tutoring systems

The demand for education in the area of simulation is in the increase. This paper describes how education in the field of simulation can take advantage of the virtues of intelligent tutoring with respect to enhancing the educational process. For this purpose, this paper gives an overview of what constitutes the objectives and the content of a comprehensive course in discrete event simulation. The architecture of an intelligent tutoring system is presented and it is discussed how these sophisticated learning aids offer individualised student guidance and support within a learning environment. The paper then introduces a prototype intelligent tutoring system, the simulation tutor, and suggests how the system might be developed to enhance education in simulation

Entrepreneurship in American Higher Education

Presents recommendations by the Kauffman Panel on Entrepreneurship Curriculum in Higher Education on making entrepreneurship a key element in the curriculum, co-curriculum activities, and university management. Includes profiles of innovative programs