Rapport : a fact-based question answering system for portuguese

Question answering is one of the longest-standing problems in natural language processing. Although natural language interfaces for computer systems can be considered more common these days, the same still does not happen regarding access to specific textual information. Any full text search engine can easily retrieve documents containing user specified or closely related terms, however it is typically unable to answer user questions with small passages or short answers. The problem with question answering is that text is hard to process, due to its syntactic structure and, to a higher degree, to its semantic contents. At the sentence level, although the syntactic aspects of natural language have well known rules, the size and complexity of a sentence may make it difficult to analyze its structure. Furthermore, semantic aspects are still arduous to address, with text ambiguity being one of the hardest tasks to handle. There is also the need to correctly process the question in order to define its target, and then select and process the answers found in a text. Additionally, the selected text that may yield the answer to a given question must be further processed in order to present just a passage instead of the full text. These issues take also longer to address in languages other than English, as is the case of Portuguese, that have a lot less people working on them. This work focuses on question answering for Portuguese. In other words, our field of interest is in the presentation of short answers, passages, and possibly full sentences, but not whole documents, to questions formulated using natural language. For that purpose, we have developed a system, RAPPORT, built upon the use of open information extraction techniques for extracting triples, so called facts, characterizing information on text files, and then storing and using them for answering user queries done in natural language. These facts, in the form of subject, predicate and object, alongside other metadata, constitute the basis of the answers presented by the system. Facts work both by storing short and direct information found in a text, typically entity related information, and by containing in themselves the answers to the questions already in the form of small passages. As for the results, although there is margin for improvement, they are a tangible proof of the adequacy of our approach and its different modules for storing information and retrieving answers in question answering systems. In the process, in addition to contributing with a new approach to question answering for Portuguese, and validating the application of open information extraction to question answering, we have developed a set of tools that has been used in other natural language processing related works, such as is the case of a lemmatizer, LEMPORT, which was built from scratch, and has a high accuracy. Many of these tools result from the improvement of those found in the Apache OpenNLP toolkit, by pre-processing their input, post-processing their output, or both, and by training models for use in those tools or other, such as MaltParser. Other tools include the creation of interfaces for other resources containing, for example, synonyms, hypernyms, hyponyms, or the creation of lists of, for instance, relations between verbs and agents, using rules

Relatório de Estágio - Solução de BI Roaming Data Science (RoaDS) em ambiente Vodafone

A telecom company (Vodafone), had the need to implement a Business Intelligence solution for Roaming data across a wide set of different data sources. Based on the data visualization of this solution, its key users with decision power, can make a business analysis and needs of infrastructure and software expansion. This document aims to expose the scientific papers produced with the various stages of production of the solution (state of the art, architecture design and implementation results), this Business Intelligence solution was designed and implemented with OLAP methodologies and technologies in a Data Warehouse composed of Data Marts arranged in constellation, the visualization layer was custom made in JavaScript (VueJS). As a base for the results a questionnaire was created to be filled in by the key users of the solution. Based on this questionnaire it was possible to ascertain that user acceptance was satisfactory. The proposed objectives for the implementation of the BI solution with all the requirements was achieved with the infrastructure itself created from scratch in Kubernetes. This BI platform can be expanded using column storage databases created specifically with OLAP workloads in mind, removing the need for an OLAP cube layer. Based on Machine Learning algorithms, the platform will be able to perform the predictions needed to make decisions about Vodafone's Roaming infrastructure

Improving NLTK for Processing Portuguese

Python has a growing community of users, especially in the AI and ML fields. Yet, Computational Processing of Portuguese in this programming language is limited, in both available tools and results. This paper describes NLPyPort, a NLP pipeline in Python, primarily based on NLTK, and focused on Portuguese. It is mostly assembled from pre-existent resources or their adaptations, but improves over the performance of existing alternatives in Python, namely in the tasks of tokenization, PoS tagging, lemmatization and NER

Alexandre, "O Grande", e a informação para o planejamento estratégico.

It relates the administrative aspects that are concentrated on four principles – planning, organization, leadership and human resources, and control – mastery used by Alexander, the Great on his conquests of Persian Empire and Asia. It shows, by general way each one of the four principles and how they were used by Alexander even before he was crowned king of Macedonia. A bigger attention is given to information, communication and logistic aspects that were used by Alexander’s forces in the war

The influence of Amazon on E-Commerce Industry Evolution and Customers’ Buying Behaviour: A case study of a financial institution

Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThe definition of e-commerce stands by a business model that allows companies and individuals to buy and sell goods and services over the Internet (Bloomenthal, 2022). Amazon remains one of the largest companies in the E-Commerce industry market. How is it possible to know this? The answer is simple, Amazon has made public its revenue of at least $75.45 billion during the current pandemic. Along with its impressive sales numbers, Amazon has once again proven to be one of the most powerful companies within the industry because of its high popularity among consumers. The main objective of this internship report is to understand what is the impact of Amazon on E-Commerce Industry and consumers’ buying behaviour, and for that it is necessary to understand what is the impact of Amazon on the main results of companies that sell products in that same platform. To answer this question, I had to understand data from Amazon Seller Central, company/brands reports, and reports of campaigns carried out. All the information was analysed using data from the company where I made my internship. It is important to say that Amazon has a lot of influence on the buying behaviour of thousands if not millions of consumers, more properly, consumers of the young generation. The reason why this is so is because, people of that age know more about technology and are more into the online world than older people. So why is this happening? Because customers love to shop online, and why? Because itis easy, comfortable, effortless and often comes with great discounts for the buyer.A definição de E-Commerce assenta num modelo de negócio que permite às empresas e indivíduos comprar e vender bens e serviços através da Internet (Bloomenthal, 2022). A Amazon continua a ser uma das maiores empresas no mercado da indústria do E-Commerce. Como é possível saber isso? A resposta é simples, a Amazon tornou pública a sua receita de pelo menos 75,45 mil milhões de dólares durante a atual pandemia. Deste modo, a Amazon provou uma vez mais ser uma das mais poderosas empresas dentro da indústria de E-Commerce pela elevada popularidade entre os consumidores. O principal objetivo deste relatório de estágio é compreender qual o impacto da Amazon na evolução da Indústria do E-Commerce e no comportamento de compra dos consumidores, e para tal é necessário compreender qual o impacto da Amazon nos principais resultados das empresas que vendem produtos nessa mesma plataforma. Para responder a esta pergunta, tive de compreender qual o impacto do ECommerce nos resultados dessas empresas (em geral) incluindo relatórios de empresas/marcas, e relatórios de campanhas realizadas e compreender também os dados das empresas na Amazon Seller Central. Toda essa informação foi analisada utilizando os dados da empresa em que realizei o meu estágio na Holanda. É importante dizer que a Amazon tem muita influência no comportamento de compra de milhares senão milhões de consumidores, mais propriamente, consumidores da geração jovem. A razão pela qual isso acontece é porque pessoas com essa idade sabem mais sobre tecnologia e estão “mais dentro” do mundo online do que as pessoas com mais idade. Assim sendo, porque é que isso está a acontecer? Porque os clientes adoram comprar online, e porquê? Porque é fácil, confortável, sem esforço e muitas vezes vem acompanhado com grandes e vantajosos descontos para o comprador

Using Lucene for Developing a Question-Answering Agent in Portuguese

Given the limitations of available platforms for creating conversational agents, and that a question-answering agent suffices in many scenarios, we take advantage of the Information Retrieval library Lucene for developing such an agent for Portuguese. The solution described answers natural language questions based on an indexed list of FAQs. Its adaptation to different domains is a matter of changing the underlying list. Different configurations of this solution, mostly on the language analysis level, resulted in different search strategies, which were tested for answering questions about the economic activity in Portugal. In addition to comparing the different search strategies, we concluded that, towards better answers, it is fruitful to combine the results of different strategies with a voting method