Don`t Buy A Pig In A Poke A Framework for Checking Consumer Requirements In A Data Marketplace

2021 | HICSS | Citations: 0

Authors: Lawrenz, Sebastian; Rausch, Andreas

Abstract: The 21st century is the century of data. Data is the new oil and powers many new ... Expand

Abstract: The 21st century is the century of data. Data is the new oil and powers many new applications and business models. The increasing value of data leads to the fact requires new possibilities and methods to trade with “data” as a trading good. One of these possibilities is a data marketplace, a digital e-commerce platform like eBay or Amazon, but specifically targeting data, information, and datasets. Since, other than physical trading goods, data is not so easy to verify, a framework is required to characterize data and to validate data against user requirements. This leads to a conflict between security and privacy requirements of data providers and the necessity of checking the data consumer requirements. In this paper, we discuss the specific challenges of data trading and introduce a framework to help users check their specific requirements (Data Quality) as a reference point for a purchase decision. Collapse

Topics: data integrity electronic mail data quality data protection project management

Methods: design science design artifact

Taxo-Semantics: Assessing similarity between multi-word expressions for extending e-catalogs

2017 | Decision Support Systems | Citations: 0

Authors: Angermann, Heiko; Pervez, Zeeshan; Ramzan, Naeem

Abstract: Taxonomies, also named directories, are utilized in e-catalogs to classify goods ... Expand

Abstract: Taxonomies, also named directories, are utilized in e-catalogs to classify goods in a hierarchical manner with the help of concepts. If there is a need to create new concepts when modifying the taxonomy, the semantic similarity between the provided concepts has to be assessed properly. Existing semantic similarity assessment techniques lack in a comprehensive support for e-commerce, as those are not supporting multi-word expressions, multilingualism, the import/export to relational databases, and supervised user-involvement. This paper proposes Taxo-Semantics, a decision support system that is based on the progress in taxonomy matching to match each expression against various sources of background knowledge. The similarity assessment is based on providing three different matching strategies: a lexical-based strategy named Taxo-Semantics-Label, the strategy Taxo-Semantics-Bk, which is using different sources of background knowledge, and the strategy Taxo-Semantics-User that is providing user-involvement. The proposed system includes a translating service to analyze non-English concepts with the help of the WordNet lexicon, can parse taxonomies of relational databases, supports user-involvement to match single sequences with WordNet, and is capable to analyze each sequence as (sub)-taxonomy. The three proposed matching strategies significantly outperformed existing techniques. Taxo-Semantics-Label could improve the accuracy result by more than 7% as compared to state-of-the-art lexical techniques. Taxo-Semantics-Bk could improve the accuracy compared to structure-based techniques by more than 8%. And, Taxo-Semantics-User could additionally increase the accuracy by on average 23%. Collapse

Topics: database system knowledge representation participatory design decision support system Prolog

Methods: machine learning WordNet design methodology experiment computational algorithm

Utopia in the solution of the Bucket Order Problem

2017 | Decision Support Systems | Citations: 0

Authors: Aledo, Juan A.; Gámez, José A.; Rosete, Alejandro

Abstract: This paper deals with group decision making and, in particular, with rank aggreg ... Expand

Abstract: This paper deals with group decision making and, in particular, with rank aggregation, which is the problem of aggregating individual preferences (rankings) in order to obtain a consensus ranking. Although this consensus ranking is usually a permutation of all the ranked items, in this paper we tackle the situation in which some items can be tied, that is, the consensus shows that there is no preference among them. This problem has arisen recently and is known as the Optimal Bucket Order Problem (OBOP). In this paper we propose two improvements to the standard greedy algorithm usually considered to approach the bucket order problem: the Bucket Pivot Algorithm (BPA). The first improvement is based on the introduction of the Utopian Matrix, a matrix associated to a pair order matrix that represents the precedences in a collection of rankings. This idealization constitutes a superoptimal solution to the OBOP, which can be used as an extreme (sometimes feasible) best value. The second improvement is based on the use of several items as pivots to generate the bucket order, in contrast to BPA that only uses a single pivot. The set of items playing the role of decision-maker is dynamically created. We analyze separately the contribution of each improvement and also their joint effect. The statistical analysis of the experiments carried out shows that the combined use of both techniques is the best choice, showing a significant improvement in accuracy (17%) with respect to the original BPA and providing an important reduction in the variance of the output. Moreover, we provide decision rules to help the decision maker to select the right algorithm according to the problem instance. Collapse

Topics: database system decision making Prolog personal computer

Methods: computational algorithm experiment descriptive statistic trade-off analysis method TOPSIS

PROCESS ANALYSIS AS FIRST STEP TOWARDS AUTOMATED BUSINESS SECURITY

2016 | European Conference On Information Systems | Citations: 0

Authors: Zahoransky, Richard; Holderer, Julius; Lange, Adrian; Brenig, Christian

Abstract: Companies are promoting the implementation of automation in business processes t ... Expand

Abstract: Companies are promoting the implementation of automation in business processes to face the high level of competitive pressure induced in the course of globalization and interconnected environments. Additionally, a series of corporate scandals obliges companies to implement regulatory and legally binding rules. Required compliance analysis of those bindings is costly and time consuming, eating up the previously gained competitive advance. Our toolkit SWAT meets this contradiction by introducing automatic compliance analysis techniques. It provides a pattern based analysis approach with predefined patterns that contain security and compliance statements which are easily reusable. This approach allows subsequent analyses with minimal user interaction as a first step towards an automatic contemporary compliance analysis of workflows. Based on mathematically sound analysis techniques, our tool graphically shows violation examples for effortless interpretation of analysis results and identification of inconformities. In this paper we present the possibilities of our toolkit to analyse process models as well as process logs. We demonstrate its underlying techniques and concepts on a real world ordering process. Collapse

Topics: business process management knowledge base Prolog access control ease of use

Methods: process log business process modeling Petri net modeling language simulation

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

2015 | Decision Support Systems | Citations: 1

Authors: Pinto, Tiago; Barreto, João; Praça, Isabel; Sousa, Tiago M.; Vale, Zita; Solteiro Pires, E. J.

Abstract: The energy sector has suffered a significant restructuring that has increased th ... Expand

Abstract: The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach. Collapse

Topics: decision support artificial intelligence database system Prolog logic programming language

Methods: meta learning simulation case study computational algorithm k-means clustering

Arguing over Goals for Negotiation: Adopting an Assumption-Based Argumentation Decision Support System

2014 | Group Decision and Negotiation | Citations: 0

Authors: Morge, Maxime; Mancarella, Paolo

Abstract: Computational models of argumentation has been put forward as a promising approa ... Expand

Abstract: Computational models of argumentation has been put forward as a promising approach to support decision making. In this context several recent works have proposed argumentation-based frameworks for decision making. In this paper we describe an application based on an argumentation-based mechanism for decision-making to concede. Adopting the assumption-based approach of argumentation, we propose an argumentation framework in which preferences are attached to goals. Arguments are defined as tree-like structures. Our framework is equipped with a computational counterpart for solving a decision problem, modeling the intuition that high-ranked goals are preferred to low-ranked goals which can be withdrawn. In this way, our framework suggests some decisions and provides an interactive and intelligible explanation of this choice. Our implementation, called MARGO, has been used for service selection within the ArguGRID project. We illustrate our approach with an industrial application, and illustrate the operation of the system with a running example. Collapse

Topics: decision making Prolog procurement management logic programming language resource allocation

Methods: chatbot literature study

Theories: game theory

A PAM approach to handling disruptions in real-time vehicle routing problems

2013 | Decision Support Systems | Citations: 0

Authors: Hu, Xiangpei; Sun, Lijun; Liu, Linlin

Abstract: During the urban distribution process, unexpected events may frequently result i ... Expand

Abstract: During the urban distribution process, unexpected events may frequently result in disruptions to the current distribution plan, which need to be handled in real-time vehicle routing. In this paper, a knowledge-based modeling approach, PAM (disruption-handling Policies, local search Algorithms and object-oriented Modeling), is developed, which combines the scheduling knowledge of experienced schedulers with the optimization knowledge concerning models and algorithms in the field of Operations Research to obtain an effective solution in real time. Experienced schedulers can respond to different disruptions promptly with heuristic adjustment based on their experience, but their solutions may be inaccurate, inconsistent, or even infeasible. This method is limited when the problem becomes large-scale. The model-algorithm method can handle large-scale problems, but it has to predefine a specific disruption and a specific distribution state for constructing a model and algorithm, which is inflexible, time-consuming and consequently unable to promptly obtain solutions for responding to different disruptions in real time. PAM modeling approach combines the advantages and eliminates the disadvantages of the two methods aforementioned. Computational experiments show that solutions achieved by this modeling approach are practical and the speed of achieving the solutions is fast enough for responding to disruptions in real time. Collapse

Topics: Prolog website Microsoft Windows operating system computer hardware

Methods: computational algorithm experiment vehicle routing problem operations research optimization model

Semantic information and knowledge integration through argumentative reasoning to support intelligent decision making

2013 | Information Systems Frontiers | Citations: 5

Authors: Janjua, Naeem Khalid; Hussain, Farookh Khadeer; Hussain, Omar Khadeer

Abstract: The availability of integrated, high quality information is a pre-requisite for ... Expand

Abstract: The availability of integrated, high quality information is a pre-requisite for a decision support system (DSS) to aid in the decision-making process. The introduction of semantic web ensures the seamless integration of information derived from diverse sources and transforms the DSS to an adoptable and flexible Semantic Web-DSS (Web-DSS). However, due to the monotonic nature of the layered development of semantic web, it lacks the capability to represent, reason and integrate incomplete and conflicting information. This, in turn, renders an enterprise incapable of knowledge integration; that is, integration of information about a subject that could potentially be incomplete, inconsistent and distributed among different Web-DSS within or across enterprises. In this article, we address the issues of incomplete and inconsistent semantic information and knowledge integration by using argumentation and argumentation schemes. We discuss the Argumentation-enabled Information Integration Web-DSS (Web@IDSS) along with its syntax and semantics for semantic information integration, and devise a methodology for sharing the results of Web@IDSS in Argument Interchange Format (AIF) format. We also discuss Argumentation-enabled Knowledge Integration Web-DSS (Web@KIDSS) for semantic knowledge integration. We provide formal syntax and semantics for the Web@KIDSS, propose a conceptual framework, and describe it in detail. We present the algorithms for knowledge integration and the prototype application for validation of results. Collapse

Topics: decision support system knowledge representation decision making intranet semantic web

Methods: computational algorithm case study ontological modelling design artifact business process modeling

A Conceptual Information Model for a ‘Green Economy Tourism System’ (GETS)

2013 | Americas Conference on Information Systems | Citations: 0

Authors: McGrath, G Michael; Lipman, Geoffrey H

Abstract: Many tourism destinations are currently pursuing green growth strategies but the ... Expand

Abstract: Many tourism destinations are currently pursuing green growth strategies but the development of appropriate policies is a complex task and, consequently, decision support technologies can be used to advantage here. The design and use of one such decision support system (DSS) is described in this paper. Key features of the system are that its design is underpinned both by a need to effectively manage the inherent complexity of the analysis domain and to allow iterative development with minimum impact on previous versions (i.e. to minimize ongoing maintenance costs). A key to realizing both these objectives is the use of a highly-abstracted conceptual information model and this is the major focus of this paper. Collapse

Topics: decision support system Prolog climate change programming language high level language

Methods: data modeling conceptual modelling design artifact action research case study

Reviews

2010 | International Journal of Information Management | Citations: 0

Authors: Fitz-Gerald, Stuart

Abstract: ... Expand

Abstract: Collapse

Topics: Java Prolog Pascal Algol

Methods: design science unified modeling language capability maturity model