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22nd IFAC Conference on Technology, Culture and International Stability (TECIS)

作者： Ivanova, Valentina Chivarov, Nayden Staikova, Maya Bulgarian Acad Sci Inst Informat & Commun Technol Sofia Bulgaria

The article proposes a stepwise evolution of an algorithmic software solution for purchase order recognition to an AI upgraded system to improve the overall data extraction accuracy and to minimize the need for human ... 详细信息

关键词： business data processing knowledge-based systems machine learning robotic process automation software algorithms

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Rule-Based business data processing in Service Coordination Systems 9

Rule-Based Business Data Processing in Service Coordination ...

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International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA)

作者： Yuan, Jie Qiu, Lirong Minzu Univ China Informat Technol Sch Beijing Peoples R China

ISBN: (纸本)9781479941735

How to make software developers focus on building the basic infrastructure and enabling environment and the business users themselves configure the resources to fulfill their certain requirements is critical. To support rapid service coordination system, the method of redesigning and redeploying is needed. business events are changes of state in enterprises or business correlated cases under the condition that the expected changes fail to appear. In this paper, we propose a rule-based business data processing method with event management in service coordination systems.

关键词： service coordination system event management business data processing rule-based system

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Combining Software Algorithms and Machine Learning in business data processing

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IFAC-PapersOnLine 2024年第3期58卷 198-202页

作者： Valentina Ivanova Nayden Chivarov Maya Staikova Institute of Information and Communication Technology Bulgarian Academy of Sciences

关键词： business data processing knowledge-based systems machine learning robotic process automation software algorithms

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Rule-Based business data processing in Service Coordination Systems

Rule-Based Business Data Processing in Service Coordination ...

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International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

作者： Jie Yuan Lirong Qiu Information technology school Minzu University of China Beijing China

ISBN: (纸本)9781479978731

关键词： business data processing Educational institutions Investment Software Buildings Organizations

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A data-flow language for specifying business data processing applications 81

A data-flow language for specifying business data processing...

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Proceedings of the 1981 conference on Functional programming languages and computer architecture

作者： Vishv M. Malhotra V. Rajaraman Computer Science Proqram Indian Institute of Technoloy Kanpur (208 016) India

ISBN: (纸本)9780897910606

A high level specification language called business data-Flow Language (BDFL) based on the data-flow model of computation is described in this paper. A translator to convert BDFL specifications into COBOL programs has been implemented. A novel feature of the proposed translation system is the use of data Base Management System (DBMS) in conjunction with COBOL. This relieves the user of the need to define data structures for the intended data processing application.

关键词： Translation DBMS Specification languages business data processing Non-procedural languages data-flow languages

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data-driven business process similarity

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IET SOFTWARE 2017年第6期11卷 309-318页

作者： Amiri, Mohammad Javad Koupaee, Mahnaz Univ Calif Santa Barbara Dept Comp Sci Santa Barbara CA 93106 USA

Although measuring the similarity of business processes based on activity labels, structural and behavioural factors can be effective, defining inexact and incomplete labels and the existence of multiple labels for similar activities cause challenges for determining similar processes. Recent attempts to consider data in business process management and the support of data modelling in business process standards have led to the creation of multiple business models with data access. In this study, a method considering data for measuring business process similarity is presented in which first the similarity of activities is measured according to their structures and behaviours in a process and also their data access. Then based on the similarity of activities, the similarity of processes is determined using the proposed algorithm.

关键词： business data processing business process re-engineering data models information retrieval pattern matching

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business Roles in the Emerging Open-data Ecosystem

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IEEE SOFTWARE 2016年第5期33卷 54-59页

作者： Lindman, Juho Kinnari, Tomi Rossi, Matti Hanken Sch Econ Informat Syst Sci Helsinki Finland Aalto Univ Sch Business Espoo Finland Aalto Univ Sch Business Informat Syst Espoo Finland

Software specialists know the merits of information visualizations, mashups, and other types of open- data enrichments. Commercial services based on these enrichments hold potential as new businesses. A proposed model... 详细信息

关键词： business data processing data Handling business Role Open data Ecosystem Information Visualization Software Specialists Customer Needs data Resources Computer Applications data Models Software Development data Mining data Visualization Mobile Communication data databases business Computer Applications Software Development Software Engineering

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One Semantic data Warehouse Fits both Electrical Vehicle data and their business Processes 17

One Semantic Data Warehouse Fits both Electrical Vehicle Dat...

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IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)

作者： Royer, Kevin Bellatreche, Ladjel Jean, Stephane EDF Res & Dev Moret Sur Loing France Univ Poitiers Futuroscope LIAS ISAE ENSMA Poitiers France

ISBN: (纸本)9781479960781

Nowadays, the electric mobility (epsilon M) is one of the most attractive domains. It involves various society's actors such as politicians, environmental analysts, energy providers, customers, business partners, etc. Offering analytical tools to analyze the epsilon M activities represents a crucial issue for the involved actors. In this paper, we address this issue in the context of the usage of electrical vehicles. We focus on two main actors of epsilon M : the French energy provider EDF and the users of electrical vehicles. EDF is in charge of providing energy power for electrical vehicles equipped with sensors. To understand the behavior of end users, our first contribution is the proposition of a data warehouse solution to store the large amount of data generated by sensors. Due to the heterogeneity of sensors sources, this data warehouse is based on a domain ontology developed in a modular way. An important aspect for EDF is the exploitation of the data warehouse by the means of business processes to obtain indicators, generate invoices, etc. Usually, these processes are defined outside the data warehouse and developed by software engineers. This solution is insufficient in our context, as EDF engineers are regularly designing, modifying and refining indicators. Our second contribution consists in connecting business processes to the domain ontology and then storing them within the data warehouse to avoid costly solutions such as outsourcing or training EDF engineers. Our proposal is implemented in a real scenario developed by EDF.

关键词： business data processing data warehouses electric vehicles ontologies (artificial intelligence) EM business processes domain ontology electric mobility electrical vehicle data semantic data warehouse business Communities data warehouses Ontologies Sensors Vehicles

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Big data Topic Modeling with Mahout for Managing business Analysis Services 7

Big Data Topic Modeling with Mahout for Managing Business An...

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IEEE/SICE International Symposium on System Integration (SII)

作者： Romsaiyud, Walisa Siam Univ Grad Sch Informat Technol Bangkok 10160 Thailand

ISBN: (纸本)9781479969449

Topic modeling for big data provides a key opportunity to address the needs of data-driven businesses in a way to deliver genuine value to business users simplifying search and summary processes via the vast amount of information. Many businesses have already worked with Hadoop paradigm in order to rapidly apply computational processing to merge data from several operational systems and analyze large volumes of multi-structured data. In this paper, we extended the features of collapsed variational Bayesian (CVB) inference algorithm for Latent Dirichlet Allocation (LDA) to discover the hidden topical patterns through statistical regularities and eliminate noises on Hadoop framework. The approach captures the evolution of topics in a sequentially organized corpus of documents into two mainly phases, mapping and reducing phases. In the mapping phase the probabilistic on each word, in collected documents, is calculated by using collapsed space of latent variables and parameters for summarizing words in each topic, and reducing phase to utilize the various results from map phase while predicting a new topic model from a given trained models. The study conducts the experiments based on a Reuters-21578 text categorization collection corpus on Hadoop clustering with 64 nodes to improve the computationally in a more efficient and accurate approach.

关键词： Big data belief networks business data processing distributed processing document handling inference mechanisms pattern clustering CVB Hadoop clustering Hadoop framework Hadoop paradigm LDA Mahout Reuters-21578 text categorization collection corpus big data topic modeling business analysis service management collapsed variational Bayesian inference algorithm computational processing data-driven businesses hidden topical patterns latent dirichlet allocation map phase multistructured data operational systems sequentially organized documents corpus statistical regularities Analytical models Bayes methods data models Hidden Markov models Inference algorithms Probabilistic logic Text categorization big data Inference algorithms electronic document handling Text categorization PVB protocol business data processing Inference mechanisms Probabilistic logic Bayesian networks data models Distributed processing Bayes methods Hidden Markov models laser Doppler anemometry Anterior interventricular branch of left coronary artery

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Preventive Inference Control in data-centric business Models

Preventive Inference Control in Data-centric Business Models

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2nd IEEE CS Security and Privacy Workshops (SPW)

作者： Accorsi, Rafael Mueller, Guenter Univ Freiburg Freiburg Germany

ISBN: (纸本)9781479904587

Inference control is a modern topic in data usage management, especially in the context of data-centric business models. However, it is generally not well understood how protection mechanisms could be designed to protect the users. The contributions of this paper are threefold: firstly, it describes the inference problem and relate it to protection mechanisms;secondly, it reports on a simple mechanism to provide a-priori inference protection;thirdly, it discusses on the drawbacks of such a mechanism, as well as on the acceptance it had on a preliminary, controlled field study. In particular, the study shows that, contrary to our expectations, participants prefer an a-posteriori approach based upon audits to detect whether inferences happened.

关键词： business data processing data privacy

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