Collecting Open Source Intelligence via Tailored Information Delivery Systems

The Internet offers a plethora of freely available information for possible use in Open Source Intelligence (OSINT) operations. However, along with this information come challenges in finding relevant information and overcoming information overload. This paper presents the results of an ongoing research in a Tailored Information Delivery Services (TIDS) system that aids users in retrieving relevant information through various open intelligence sources. The TIDS provides a semantics-based query constructor that operates in a “What You Get is What You Need (WYGIWYNTM)” fashion and builds ontology based information tagging, theme extractor, and contextual model

A Coherent Measurement of Web-Search Relevance

We present a metric for quantitatively assessing the quality of Web searches. The relevance-of-searching-on-target index measures how relevant a search result is with respect to the searcher\u27s interest and intention. The measurement is established on the basis of the cognitive characteristics of common user\u27s online Web-browsing behavior and processes. We evaluated the accuracy of the index function with respect to a set of surveys conducted on several groups of our college students. While the index is primarily intended to be used to compare the Web-search results and tell which is more relevant, it can be extended to other applications. For example, it can be used to evaluate the techniques that people apply to improve the Web-search quality (including the quality of search engines), as well as other factors such as the expressiveness of search queries and the effectiveness of result-filtering processes

Fuzzy Model for Quantitative Assessment of Environmental Start-up Projects in Air Transport

The purpose of this paper is to develop an applied fuzzy model of information technology to obtain quantitative estimates of environmental start-up projects in air transport. The developed model will become a useful tool for venture funds, business angels, or crowdfunding platforms for the development of innovative air transport businesses. Obtaining a quantitative estimate of the environmental start-up projects will increase the sustainability of the decision making on the security of financing of such projects by investors. This article develops a fuzzy evaluation model of project start-ups in air transport as an application of our neuro-fuzzy model in a specific air transport environment. The applied model provides output ranking of start-up project teams in air transport based on a four-layer neuro-fuzzy network. The presented model declares the possibilities of the application to solve these economic problems and offers the space for subsequent research focused on its usability in several areas of start-up development, in sectors and processes differentiated. The benefits are also visible for several types of policies, with an emphasis on decision-making processes in regulatory mechanisms to support the state funding in Slovakia, the EU etc. Document type: Articl

A Fuzzy Model of Risk Assessment for Environmental Start-Up Projects in the Air Transport Sector

The purpose of this paper is to develop a fuzzy model of the risk assessment for environmental start-up projects in the air transport sector at the stage of business expansion. The model developed for the following software will be a useful tool for the risk decision support system of investment funds in financing environmental start-up projects at the stage of market conquest. Developing a quantitative risk assessment for environmental start-up projects for the air transport sector will increase the resilience of making risk decisions about their financing by the investors. In this paper, a set of 21 criteria for assessing the risk of launching environmental start-up projects in the air transport sector were formulated for the first time by presenting inputs in the form of a linguistic risk assessment and the number of credible expert considerations. The fuzzy risk assessment model, based on expert knowledge, uses linguistic variables, reveals the uncertainty of the input data, and displays a risk assessment with linguistic interpretation. The result of the paper is a fuzzy model that is embedded in a generalized algorithm and tested in an example risk assessment of environmental start-up projects in the air transport sector