Vaibhav Jain

Nadmierne przeciążenie informacyjne stalo się ostatnio poważnym problemem. Powszechne stosowanie technologii ulatwilo życie, ale doprowadzilo r wnież do latwego dostępu do tworzenia informacji. Istnieje kilka portali informacyjnych, na kt re codziennie trafia wiele informacji. W erze e-wiadomości czytanie wiadomości online stalo się powszechnym nawykiem. Ludzie chętniej czytają wiadomości w Internecie niż w gazetach lub innych mediach. Użytkownikom coraz trudniej jest znaleźc interesujące i popularne wiadomości w kr tkim czasie. Obecnie stalo się to kluczowym wyzwaniem, ponieważ każdy ma inne upodobania i nawyki czytelnicze. Rozwiązaniem tego problemu jest system rekomendacji wiadomości. Opracowano system rekomendacji oparty na treści, kt ry rekomenduje wiadomości na podstawie podobieństwa artykul w do zapytania i podobieństwa dokument w. Do określenia podobieństwa zapytania w calym korpusie artykul w informacyjnych wykorzystuje się takie miary, jak częstotliwośc występowania termin w i podobieństwo dokument w. Każdy dokument jest por wnywany z każdym dokumentem dostępnym w korpusie, a następnie przeprowadzane jest dopasowanie treści w celu ustalenia wyniku podobieństwa. Wyniki są oceniane na dw ch r żnych zestawach danych przy użyciu miar slużących do oceny trafności rekomendowanych artykul w informacyjnych.

A sobrecarga excessiva de informa es tornou-se um problema grave recentemente. O uso extensivo da tecnologia facilitou a vida, mas tamb m levou ao acesso cria o de informa es. Existem v rios portais de not cias onde muitas informa es s o carregadas diariamente. Como estamos na era das not cias eletr nicas, ler not cias online tornou-se um h bito comum das pessoas. As pessoas tendem a ler not cias na Web em vez de jornais ou outros meios de comunica o. Torna-se mais dif cil para o utilizador encontrar not cias relevantes e populares em pouco tempo. Hoje em dia, isso tornou-se um grande desafio, pois todos t m gostos e h bitos de leitura diferentes. Uma solu o para este problema o sistema de recomenda o de not cias. Foi desenvolvida uma recomenda o baseada em conte do que recomenda not cias com base na semelhan a do artigo com a consulta e na semelhan a do documento. Medidas como contagem de frequ ncia de termos e semelhan a de documentos s o usadas para descobrir a semelhan a da consulta no corpus completo de artigos de not cias. Cada documento comparado com todos os documentos dispon veis no corpus e a correspond ncia de conte do realizada para descobrir a pontua o de semelhan a. Os resultados s o avaliados em dois conjuntos de dados diferentes usando medidas para avaliar a relev ncia dos artigos de not cias recomendados.

Die berm ige Informationsflut ist in letzter Zeit zu einem ernsthaften Problem geworden. Der umfassende Einsatz von Technologie hat das Leben erleichtert, aber auch den Zugang zur Erstellung von Informationen erm glicht. Es gibt mehrere Nachrichtenportale, auf denen t glich eine Vielzahl von Informationen hochgeladen wird. In Zeiten von E-News ist das Lesen von Online-Nachrichten f r viele Menschen zur Gewohnheit geworden. Die Menschen lesen Nachrichten eher im Internet als in Zeitungen oder anderen Medien. F r Nutzer wird es immer schwieriger, in kurzer Zeit relevante und beliebte Nachrichten zu finden. Da jeder Mensch unterschiedliche Vorlieben und Lesegewohnheiten hat, ist dies heute eine gro e Herausforderung. Eine L sung f r dieses Problem ist ein Nachrichtenempfehlungssystem. Es wurde ein inhaltsbasiertes Empfehlungssystem entwickelt, das Nachrichten auf der Grundlage der hnlichkeit von Artikeln mit Suchanfragen und der hnlichkeit von Dokumenten empfiehlt. Ma nahmen wie die H ufigkeit von Begriffen und die hnlichkeit von Dokumenten werden verwendet, um die hnlichkeit von Suchanfragen im gesamten Korpus von Nachrichtenartikeln zu ermitteln. Jedes Dokument wird mit jedem im Korpus verf gbaren Dokument verglichen und ein Inhaltsabgleich durchgef hrt, um den hnlichkeitsgrad zu ermitteln.

Os outliers s o considerados como dados ruidosos nas estat sticas, revelou-se um problema importante que est a ser investigado em diversos campos de investiga o e dom nios de aplica o. Muitas t cnicas de detec o de outliers foram desenvolvidas especificamente para certos dom nios de aplica o, enquanto que algumas t cnicas s o mais gen ricas. Alguns dom nios de aplica o est o a ser pesquisados em estrita confidencialidade, como a investiga o sobre crime e actividades terroristas. As t cnicas e os resultados de tais t cnicas n o s o prontamente divulgados. As grandes an lises de dados tornaram-se muito populares no cen rio actual e a manipula o de grandes dados ganhou a grande aten o dos investigadores no campo da an lise de dados. A computa o em nuvem fornece recursos infra-estruturais poderosos e econ micos para os utilizadores da nuvem lidarem com grandes dados cada vez maiores com estruturas de processamento de dados tais como MapReduce. Este trabalho considera dois algoritmos de clustering conhecidos como DBScan e K-Means e implementados com o conjunto de dados Sensed da Intel Corporation.

With ServiceNow, it has become easier than before to manage IT operations by keeping a track of the incidents, event logging, asset and application licensing management, help desk for troubleshooting with knowledge base articles supported over cloud etc. All these operations embedded within a single web application supporting desktop and mobile platforms drill down the costs of IT based companies to a huge extent and makes everyday jobs easier and efficient.

With the advancement of new and better technologies, it was realized soon enough that there is a dire need to be more productive to meet the ever-growing market demands and keep up with the pace. One with the mindset of being flexible and adaptive gets to rule the market, while others get entangled in the same dead-end job. As complexities increased, it was soon realized by the IT firms that there is a desperate need to being more productive and delegate the old manual tasks to machines and computer systems. Software Robots is the 'The New Norm' of achieving optimized results for our daily IT application tasks. It releases us from the limitation of being in front of a computer to perform repetitive system operations. It marks the beginning of Artificially Intelligent bots, which are nothing but a virtual workforce that can make decisions by itself, incorporating some cognitive abilities. Robotics Process Automation is the domain that deals with rule-driven software robots which work under the provided circumstances, evaluates all conditions programmed in it and responds accordingly. It can handle all types of non-productive admin tasks with ease and achieve exponential efficiency. It mimics the IT operations in the same way as a human would do, sitting in front of a computer system.

Outliers are regarded as noisy data in statistics, has turned out to be an important problem which is being researched in diverse fields of research and application domains. Many outlier detection techniques have been developed specific to certain application domains, while some techniques are more generic. Some application domains are being researched in strict confidentiality such as research on crime and terrorist activities. The techniques and results of such techniques are not readily forthcoming. Big data analysis has become much popular in the present day scenario and the manipulation of big data has gained the keen attention of researchers in the field of data analytics. Cloud computing provides powerful and economical infrastructural resources for cloud users to handle ever-increasing Big Data with data-processing frameworks such as MapReduce. This work consider two clustering algorithms known as DBScan and K-Means and implemented with Intel Corporation's Sensed dataset.

INTRODUCTIONIT SEEMS A THING OF THE PAST that you had to do all the manual work repetitively in a firm, surging only your stress, monotony and nothing in terms of your knowledge, skillset and cleverness. With progression of information technology in today's era, the ask from professionals is to work smarter and not just harder. Developers are inclined to learn more sophisticated and better tools and not stay working in the same dead-end job. This is where the realization of automating the repetitive manual processes came into picture. Optimization of your work and effort needed in it would ultimately result in a more productive use of your time. And just like other technology developments, this didn't happen overnight as well. It took years of research, prototypes, small niche products that ultimately led to the formulation of software robots. The term "Robots" has been prevailing for decades in our community and has a connotation of mechanical parts, when put together, accomplish their assigned tasks. For this, let me make it clear that this book is not going to deal with such Hardware robots. It's not a physical device sitting in front of your system doing work for you. Robots have disparate conformations. A computer in itself is a robot, providing you the capability to create, maintain and remove your documents. Similarly, a phone can be termed as bot providing capabilities to make calls, work on business software applications utilizing touch interfaces any many more. Just a couple of years back, for people like us, it was difficult for comprehend the fact that doing a full-fledged accounting and management business over a PC system would be possible. But in today's world, you would see even toddlers handling refined IT products such as laptops, i-phones, smartwatches etc. with ease. Software Robots or Robotics Process Automation is the process of imitating the job a normal person would do in front of a computer system. It is the first step to building the Artificially Intelligent operations, which would be nothing but programmed bots accompanied with cognitive abilities. RPA provides an advanced substitute to improve productivity while being cost-effective and accurate through automation of rule-based, back-end administrative processes. When several bots work together in an office environment, this arrangement is called "virtual workforce". The virtual workforce is deployed via an operational team and is usually managed by the firm employees who implemented it. There are quite a few vendors in market today providing tools with various automation capabilities. The major ones among these include: UiPath, BluePrism, Automation Anywhere, IP Soft, WorkFusion, NICE, BlueWorks Live, Exilant, Xerox, Celaton, PEGA Systems and Kofax. In this book, we'll be dealing with UiPath, one of the most sophisticated tools available today that delivers basic, desktop, web and citrix based automations.