Real-time tracking and mining of users’ actions over social media

© 2020, ComSIS Consortium. All rights reserved. With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about what, when, and how to respond to users’ actions over social media. Questions that Social Miner allows to answer include what actions were frequently executed and why certain actions were executed more than others

Meta-Estudio de BPM en e-GOV

La aplicación del paradigma BPM (Business Process Management) en las organizaciones presenta distintos grados de madurez, siendo el sector privado un espacio donde su aplicación está más consolidada. Los beneficios de utilización de BPM en organizaciones gubernamentales lleva a dicho ámbito muchos de los beneficios del paradigma, siendo los más importantes el modelado de los principales circuitos de la administración y la automatización de los mismos para poder monitorear y evaluar, cerrando un ciclo de mejora continua. El propósito de este trabajo es vincular los conceptos de e-gov – entendido en líneas generales como la aplicación de TIC a los ámbitos gubernamentales- y BPM, a través de un meta-estudio que parte de un análisis bibliográfico y realiza una conceptualización que surge de un conjunto de preguntas de investigación.Sociedad Argentina de Informática e Investigación Operativ

Täpne ja tõhus protsessimudelite automaatne koostamine sündmuslogidest

Töötajate igapäevatöö koosneb tegevustest, mille eesmärgiks on teenuste pakkumine või toodete valmistamine. Selliste tegevuste terviklikku jada nimetatakse protsessiks. Protsessi kvaliteet ja efektiivsus mõjutab otseselt kliendi kogemust – tema arvamust ja hinnangut teenusele või tootele. Kliendi kogemus on eduka ettevõtte arendamise oluline tegur, mis paneb ettevõtteid järjest rohkem pöörama tähelepanu oma protsesside kirjeldamisele, analüüsimisele ja parendamisele. Protsesside kirjeldamisel kasutatakse tavaliselt visuaalseid vahendeid, sellisel kujul koostatud kirjeldust nimetatakse protsessimudeliks. Kuna mudeli koostaja ei suuda panna kirja kõike erandeid, mis võivad reaalses protsessis esineda, siis ei ole need mudelid paljudel juhtudel terviklikud. Samuti on probleemiks suur töömaht - inimese ajakulu protsessimudeli koostamisel on suur. Protsessimudelite automaatne koostamine (protsessituvastus) võimaldab genereerida protsessimudeli toetudes tegevustega seotud andmetele. Protsessituvastus aitab meil vähendada protsessimudeli loomisele kuluvat aega ja samuti on tulemusena tekkiv mudel (võrreldes käsitsi tehtud mudeliga) kvaliteetsem. Protsessituvastuse tulemusel loodud mudeli kvaliteet sõltub nii algandmete kvaliteedist kui ka protsessituvastuse algoritmist. Antud doktoritöös anname ülevaate erinevatest protsessituvastuse algoritmidest. Toome välja puudused ja pakume välja uue algoritmi Split Miner. Võrreldes olemasolevate algoritmidega on Splint Miner kiirem ja annab tulemuseks kvaliteetsema protsessimudeli. Samuti pakume välja uue lähenemise automaatselt koostatud protsessimudeli korrektsuse hindamiseks, mis on võrreldes olemasolevate meetoditega usaldusväärsem. Doktoritöö näitab, kuidas kasutada optimiseerimise algoritme protsessimudeli korrektsuse suurendamiseks.Everyday, companies’ employees perform activities with the goal of providing services (or products) to their customers. A sequence of such activities is known as business process. The quality and the efficiency of a business process directly influence the customer experience. In a competitive business environment, achieving a great customer experience is fundamental to be a successful company. For this reason, companies are interested in identifying their business processes to analyse and improve them. To analyse and improve a business process, it is generally useful to first write it down in the form of a graphical representation, namely a business process model. Drawing such process models manually is time-consuming because of the time it takes to collect detailed information about the execution of the process. Also, manually drawn process models are often incomplete because it is difficult to uncover every possible execution path in the process via manual data collection. Automated process discovery allows business analysts to exploit process' execution data to automatically discover process models. Discovering high-quality process models is extremely important to reduce the time spent enhancing them and to avoid mistakes during process analysis. The quality of an automatically discovered process model depends on both the input data and the automated process discovery application that is used. In this thesis, we provide an overview of the available algorithms to perform automated process discovery. We identify deficiencies in existing algorithms, and we propose a new algorithm, called Split Miner, which is faster and consistently discovers more accurate process models than existing algorithms. We also propose a new approach to measure the accuracy of automatically discovered process models in a fine-grained manner, and we use this new measurement approach to optimize the accuracy of automatically discovered process models.https://www.ester.ee/record=b530061

A benefit-oriented framework for the decision-making process on the application of KMS in SME

The result of the presented PhD project is an artifact providing the SME practitioner with the KinS conceptual framework including method support. Therefore concepts from KM and KMS are newly combined and validated applying the perceived benefit approach of the KMS Success Model. The KinS framework uses the demand for support as the starting point for the perceived benefit and analyzes it with regard to the support opportunities by knowledge services. With the help of the framework, the gap in the knowledge base can be addressed and benefit-orientation in the KMS support can be provided

A capability-based context modelling method to enhance digital service flexibility

The thesis argues that the enterprises need to understand their application context to be able to offer flexible digital services. Furthermore, after analysing the state of research in Services Science, it concludes that different roles with varying backgrounds participate to design and implementation of digital services, which adds the need for alignment between those as a further challenge for flexibility. To fulfil this, the thesis designs a context modelling method and evaluates it by means of Design Science Research (DSR).Digitalisierung in der Dienstleistungökonomie erfordert, die Auswirkungen von veränderten Anwendungskontexten an die zu erbringenden Services genau zu verstehen. Es wird nach der Analyse des Standes der Technik in Services Science festgestellt, dass unterschiedliche Rollen in der Gestaltung und Umsetzung von Digital Services beteiligt sind, was die Notwendigkeit der Abstimmung zwischen diesen Rollen als eine wichtige Herausforderung an die Flexibilität stellt. Um ein solches Alignment zu erreichen, entwickelt dieser Beitrag eine Kontextmodellierungsmethode und evaluiert diese mittels DSR

An evaluation of the challenges of Multilingualism in Data Warehouse development

In this paper we discuss Business Intelligence and define what is meant by support for Multilingualism in a Business Intelligence reporting context. We identify support for Multilingualism as a challenging issue which has implications for data warehouse design and reporting performance. Data warehouses are a core component of most Business Intelligence systems and the star schema is the approach most widely used to develop data warehouses and dimensional Data Marts. We discuss the way in which Multilingualism can be supported in the Star Schema and identify that current approaches have serious limitations which include data redundancy and data manipulation, performance and maintenance issues. We propose a new approach to enable the optimal application of multilingualism in Business Intelligence. The proposed approach was found to produce satisfactory results when used in a proof-of-concept environment. Future work will include testing the approach in an enterprise environmen

Perspectives in Business Informatics Research 13th International Conference, BIR 2014, Lund, Sweden, September 22-24, 2014. Proceedings

This book constitutes the proceedings of the 13th International Conference on Perspectives in Business Informatics Research, BIR 2014, held in Lund, Sweden, in September 2014. Overall, 71 submissions were rigorously reviewed by 55 members of the Program Committee representing 22 countries. As a result, 27 full papers have been selected for publication in this volume. The papers cover many aspects of business information research and have been organized in topical sections on: business, people, and systems; business and information systems development; and contextualized evaluation of business informatics

Perspectives in Business Informatics Research13th International Conference, BIR 2014, Lund, Sweden, September 22-24, 2014. Proceedings /

XIV, 392 p. 107 illus.online resource