Hi, how can I help you?: Automating enterprise IT support help desks

Question answering is one of the primary challenges of natural language understanding. In realizing such a system, providing complex long answers to questions is a challenging task as opposed to factoid answering as the former needs context disambiguation. The different methods explored in the literature can be broadly classified into three categories namely: 1) classification based, 2) knowledge graph based and 3) retrieval based. Individually, none of them address the need of an enterprise wide assistance system for an IT support and maintenance domain. In this domain the variance of answers is large ranging from factoid to structured operating procedures; the knowledge is present across heterogeneous data sources like application specific documentation, ticket management systems and any single technique for a general purpose assistance is unable to scale for such a landscape. To address this, we have built a cognitive platform with capabilities adopted for this domain. Further, we have built a general purpose question answering system leveraging the platform that can be instantiated for multiple products, technologies in the support domain. The system uses a novel hybrid answering model that orchestrates across a deep learning classifier, a knowledge graph based context disambiguation module and a sophisticated bag-of-words search system. This orchestration performs context switching for a provided question and also does a smooth hand-off of the question to a human expert if none of the automated techniques can provide a confident answer. This system has been deployed across 675 internal enterprise IT support and maintenance projects.Comment: To appear in IAAI 201

Bayesian network modelling of an offshore electrical generation system for applications within an asset integrity case for normally unattended offshore installations

This article proposes the initial stages of the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore system. The main focus is the construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity. The majority of the data required to complete the Bayesian network was gathered from various databases and past risk assessment experiments and projects. However, where data were incomplete or non-existent, expert judgement was applied through pairwise comparison, analytical hierarchy process and a symmetric method to fill these data gaps and to complete larger conditional probability tables. A normally unattended installation–Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed to ensure safe operations in situations whereby physical human-to-machine interaction is not occurring. The Integrity Case can be said to be dynamic as it shall be continually updated for an installation as the quantitative risk analysis data are recorded. This allows for the integrity of the various systems and components of an offshore installation to be continually monitored. The Bayesian network allows cause and effect relationships to be modelled through clear graphical representation. The model accommodates for continual updating of failure data

Remote fabrication of integrated circuits : software support for the M.I.T. computer aided fabrication environment

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 73-74).by Jimmy Y. Kwon.M.S

A Generic Approach and Framework for Managing Complex Information

Several application domains, such as healthcare, incorporate domain knowledge into their day-to-day activities to standardise and enhance their performance. Such incorporation produces complex information, which contains two main clusters (active and passive) of information that have internal connections between them. The active cluster determines the recommended procedure that should be taken as a reaction to specific situations. The passive cluster determines the information that describes these situations and other descriptive information plus the execution history of the complex information. In the healthcare domain, a medical patient plan is an example for complex information produced during the disease management activity from specific clinical guidelines. This thesis investigates the complex information management at an application domain level in order to support the day-to-day organization activities. In this thesis, a unified generic approach and framework, called SIM (Specification, Instantiation and Maintenance), have been developed for computerising the complex information management. The SIM approach aims at providing a conceptual model for the complex information at different abstraction levels (generic and entity-specific). In the SIM approach, the complex information at the generic level is referred to as a skeletal plan from which several entity-specific plans are generated. The SIM framework provides comprehensive management aspects for managing the complex information. In the SIM framework, the complex information goes through three phases, specifying the skeletal plans, instantiating entity-specific plans, and then maintaining these entity-specific plans during their lifespan. In this thesis, a language, called AIM (Advanced Information Management), has been developed to support the main functionalities of the SIM approach and framework. AIM consists of three components: AIMSL, AIM ESPDoc model, and AIMQL. The AIMSL is the AIM specification component that supports the formalisation process of the complex information at a generic level (skeletal plans). The AIM ESPDoc model is a computer-interpretable model for the entity-specific plan. AIMQL is the AIM query component that provides support for manipulating and querying the complex information, and provides special manipulation operations and query capabilities, such as replay query support. The applicability of the SIM approach and framework is demonstrated through developing a proof-of-concept system, called AIMS, using the available technologies, such as XML and DBMS. The thesis evaluates the the AIMS system using a clinical case study, which has applied to a medical test request application

The Serums Tool-Chain:Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems

Digital technology is permeating all aspects of human society and life. This leads to humans becoming highly dependent on digital devices, including upon digital: assistance, intelligence, and decisions. A major concern of this digital dependence is the lack of human oversight or intervention in many of the ways humans use this technology. This dependence and reliance on digital technology raises concerns in how humans trust such systems, and how to ensure digital technology behaves appropriately. This works considers recent developments and projects that combine digital technology and artificial intelligence with human society. The focus is on critical scenarios where failure of digital technology can lead to significant harm or even death. We explore how to build trust for users of digital technology in such scenarios and considering many different challenges for digital technology. The approaches applied and proposed here address user trust along many dimensions and aim to build collaborative and empowering use of digital technologies in critical aspects of human society

Design and implementation of an automated data quality control system in the financial sector

[EN] Lending Controls play an important role in ensuring that banking product control standards are understood and applied. The Data Quality and Structural Systems team continuously develop and deliver operational controls within the Core Banking Platform in order to improve the performance of the business and to minimise risk and costs. The identification of existing internal controls and reporting of Data Quality in a bank and their link with automation requirements and software process improvement are in the focus of this research. Therefore, the aim is to develop an automated process and software tool that helps to improve and control internal banking processes as well as manage the data quality assessment and monitor the retrieval of the pending position status of loan processes in banks. The methodology followed is based on Software Reengineering such as Agile Methodology and Extreme Programming. The automation of Data Quality Internal Controls has proven to be a suitable process to improve the quality of data, minimising the errors and reducing the time as well as the management of the customer impact.[ES] Santander UK es parte del Grupo Santander. Es un banco comercial y de particulares con presencia en Europa, América del Norte y América del Sur. Es el segundo banco más grande de Europa con más de 1400 oficinas y 25 millones de clientes. Tiene una orientación del modelo de negocio de Santander hacia actividades de banca minorista. Lo que le hace estar más protegido frente a los cambios que se están considerando a nivel internacional en cuanto a la creación de estructuras separadas entre banca comercial y banca de inversión. Las altas direcciones de los bancos consideran que existen focos de riesgos que pueden afectar al desarrollo de su negocio y consecuentemente a los riesgos derivados del mismo. Por eso mismo la calidad de la gestión del riesgo es un eje prioritario en la actuación de un banco. El riesgo de crédito es una de las mayores preocupaciones. Es lo que puede hacer que un banco acabe en bancarrota o que le permita competir con los más poderosos. El riesgo de crédito está directamente relacionado con los controles internos. Desde que se publicó la Sabanes-­‐‑Oxley, las empresas al principio reacias a adaptarse al cambio, han visto las mejoras que supone tener una buena gestión y controles internos que junto con las auditorías internas hagan menos frecuentes las auditorías externas. Reduciendo así el coste que supone tener que resolver los conflictos durante auditorías externas. Uno de los factores más importantes de los controles internos es la calidad de los datos que se generan, almacenan y analizan. La cantidad de información que se genera hoy en día hace imprescindible una buena gestión para poder obtener un beneficio de ella. La mayoría de los trabajadores en el entorno empresarial trabaja con hojas de cálculo para procesar datos. Normalmente son tareas manuales y repetitivas que pueden generar errores y el tiempo empleado para desarrollarlas es muy elevado. El proyecto consiste en generar una herramienta de software basada en la hoja de cálculo, que permita automatizar los controles internos que se llevan a cabo dentro de la empresa. Lo que reducirá los errores y el tiempo de ejecución de las tareas. El propósito del proyecto es desarrollar un modelo técnico para controlar los diferentes procesos. Esto se realizara mediante el análisis de la situación actual, entrevistas con los expertos y la persona al cargo del proyecto, y reuniones con los usuarios del modelo actual. Con la información recopilada de la literatura, la lectura de los documentos internos y las reuniones, se configuró un gráfico de procesos que permitió localizar entender y analizar el proceso existente así como la incorporación de mejoras que lo conviertan en un modelo automatizado. Los objetivos del proyecto son: 1. Identificación de las prácticas comunes y composición de una literatura revisada para la adquisición de un profundo conocimiento de los productos bancarios, los procesos de control internos, existentes modelos de control, y mejora de procesos de software y su metodología. 2. Análisis de requisitos de los existentes productos bancarios y sus procesos mediante reuniones y entrevistas informales y revisión de literatura previa para establecer una visión clara de las mejoras necesarias y aplicaciones a desarrollar para poder incorporarlas al modelo existente. 3. Desarrollo de código usando software existente para desarrollar una herramienta modelo que automatice controles internos del banco para analizar la calidad de los datos de la base de datos. 4. Garantía de calidad de datos mediante la implementación del proceso automatizado y el software desarrollado, reduciendo el tiempo empleado y eliminando los errores potenciales en los datos. 5. Desarrollo de una herramienta de software para recuperar las cuentas con saldo pendiente en el estado de los préstamos. Esta aplicación reduce los errores que origina un software interno del banco, lo que supone una gran relevancia debido al gran impacto en el consumidor que estos errores significan. El alcance del proyecto es el desarrollo completo de una aplicación que incluya herramientas para el control interno, automatizando y mejorando el proceso de control eficientemente usando metodologías de ingeniería de software. Además de mejorar la calidad de los datos y monitorizar la recuperación de los pagos pendientes y los estados en las cuentas de préstamos.Carrión Giménez, MJ. (2013). DESIGN AND IMPLEMENTATION OF AN AUTOMATED DATA QUALITY CONTROL SYSTEM IN THE FINANCIAL SECTOR. http://hdl.handle.net/10251/47922.Archivo delegad