Search results for "Structured Data"
showing 7 items of 17 documents
Provision of tailored health information for patient empowerment: An initial study
2019
Search of "right" health information by patients/citizens is an important step towards their empowerment. The number of health information seekers on the Internet is steadily increasing over the years so it is crucial to understand their information needs and the challenges they face during the search process. However, generic search engines do not make any distinction among the users and overload them with the amount of information. Moreover, specific search engines/sites mostly work on medical literature and are built by hand. This paper analyses the possibility of providing the user with tailored web information by exploiting the web semantic capabilities and, in particular, those of sch…
Machine learning in management accounting research: Literature review and pathways for the future
2021
This paper explores the possibilities of machine learning (ML) methods in management accounting research and showcases one future avenue in practice by applying ML-based textual literature review to ML/AI research in accounting. The review reveals that machine learning methods in management accounting (MA) are still in their infancy, and current research in accounting has progressed in and focused mainly on three areas related to ML and AI: 1) effects on the field of accounting and the development of the accounting profession, 2) textual analysis related to accounting data/reports, and 3) prediction methods. Based on our literature review and recently published related ML research from othe…
On-Line Retrieval of Health Information Based on Language Complexity, Information Customization and Information Quality
2021
Abstract. A patient, nowadays, acquires on-line health information mainly by means of a search engine. Generic search engines have been shown to be limited and unsatisfactory, at times, because of their generic searches that overload users with the amount of results. Moreover, they are not able to provide customized information to different types of users. At the same time, specific search engines mostly work on medical literature and provide extracts from medical journals that are mainly useful for medical researchers and experts. As a consequence, the found health information may or may not help a user (mainly a non-expert one) for a full comprehension of what he/she is looking for (e.g.,…
On Metadata Support for Integrating Evolving Heterogeneous Data Sources
2019
With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and tran…
Data lakes in business intelligence: reporting from the trenches
2018
Abstract The data lake approach has emerged as a promising way to handle large volumes of structured and unstructured data. This big data technology enables enterprises to profoundly improve their Business Intelligence. However, there is a lack of empirical studies on the use of the data lake approach in enterprises. This paper provides the results of an exploratory study designed to improve the understanding of the use of the data lake approach in enterprises. I interviewed 12 experts who had implemented this approach in various enterprises and identified three important purposes of implementing data lakes: (1) as staging areas or sources for data warehouses, (2) as a platform for experime…
Analyzing online search patterns of music festival tourists
2020
Music festivals, as cultural events that induce tourism flows, intermediate both the cultural and travel experience. The present study analyzes online search behavior of potential attenders to a music festival. We hypothesize that the search process reveals latent patterns of behavior of cultural tourists planning to attend music festivals. To this end, information from Google Trends on queries related to three popular music festivals is used to build a network of search topics. Based on it, alternative exponential random graph model specifications are estimated. Findings support the general result of mediated information flows: music festivals induce planning and traveling queries. Howeve…