Intelligent decision support for data purchase

Martins, Denis Mayr Lima; Vossen, Gottfried; Neto, Fernando Buarque de Lima

doi:10.1145/3106426.3106434

Cited by 5 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research work proposed in Martins et al (2017) adheres to the emergence of data marketplaces as alternative to traditional data commerce as they provide appropriate online environments for data offering and purchasing. Nevertheless, as the number of available purchase datasets increases, the task of buying appropriate offers is often challenging.…”

Section: Related Workmentioning

confidence: 99%

“…Figure 11 illustrates the concept of the competitive learning algorithm (Kohonen, 2013). The SOM has been used as a purchase decision-making support in many studies (Kohara and Isomae, 2006) (Martins et al, 2017) (Kohara, 2013) (Cho et al, 2014). From this perspective, we use SOM in our recommendation system to provide users with more purchasing options by exploring new opportunities.…”

Section: Local Databasementioning

confidence: 99%

“…Research work proposed in Martins et al . (2017) adheres to the emergence of data marketplaces as alternative to traditional data commerce as they provide appropriate online environments for data offering and purchasing.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of purchasing business process in Moroccan public universities based on COBIT and artificial intelligence techniques

Sakyoud

Aaroud²,

Akodadi³

2023

View full text Add to dashboard Cite

PurposeThe main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.Design/methodology/approachThe design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.FindingsThe modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.Research limitations/implicationsBusiness limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.Practical implicationsThe modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.Originality/valueThe adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Local Databasementioning

confidence: 99%

See 1 more Smart Citation

Optimization of purchasing business process in Moroccan public universities based on COBIT and artificial intelligence techniques

Sakyoud

Aaroud²,

Akodadi³

2023

View full text Add to dashboard Cite

show abstract

“…Alternatively, querying can happen on a metadata level to query for the right data product(s) from amongst all the data products, e.g., [136]. These querying mechanisms are, of course, not mutually exclusive, and some data markets combine both types [137].…”

Section: Specialised Querying Mechanismmentioning

confidence: 99%

Data Market Design: A Systematic Literature Review

2022

View full text Add to dashboard Cite

Data markets are platforms that provide the necessary infrastructure and services to facilitate the exchange of data products between data providers and data consumers from different environments. Over the last decade, many data markets have sprung up, capitalising on the increased appreciation of the value of data and catering to different domains. In this work, we analyse the existing body of scientific literature on data markets to provide the first comprehensive overview of research into the design of data markets, regardless of scientific background or application domain. In doing so, we contribute to the field in several ways: 1) We present an overview of the state of the art in academic research on data markets and compare this with existing market trends to identify potential gaps. 2) We identify important application domains and contexts where data markets are being put into practice. 3) Finally, we provide taxonomies of both design problems for data markets and the solutions that are being investigated to address them. We conclude our work by identifying common types of data markets and corresponding best practices for designing them. The outcome of this work is intended to serve as a starting point for software architects and engineers looking to design data markets.

show abstract