904 resultados para INFORMATION EXTRACTION FROM DOCUMENTS
Resumo:
Assessment processes are essential to guarantee quality and continuous improvement of software in healthcare, as they measure software attributes in their lifecycle, verify the degree of alignment between the software and its objectives and identify unpredicted events. This article analyses the use of an assessment model based on software metrics for three healthcare information systems from a public hospital that provides secondary and tertiary care in the region of Ribeirão Preto. Compliance with the metrics was investigated using questionnaires in guided interviews of the system analysts responsible for the applications. The outcomes indicate that most of the procedures specified in the model can be adopted to assess the systems that serves the organization, particularly in the attributes of compatibility, reliability, safety, portability and usability.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
This report contains a brief discussion of the boards and commissions within this department, caseload statistics from each level of court, and concludes with personnel and other financial information gathered from the Judicial Survey of the offices of Clerk of Court, Probate Judge, Master-In-Equity, Public Defender, Magistrate and Municipal Judge.
Resumo:
A evolução tecnológica tem provocado uma evolução na medicina, através de sistemas computacionais voltados para o armazenamento, captura e disponibilização de informações médicas. Os relatórios médicos são, na maior parte das vezes, guardados num texto livre não estruturado e escritos com vocabulário proprietário, podendo ocasionar falhas de interpretação. Através das linguagens da Web Semântica, é possível utilizar antologias como modo de estruturar e padronizar a informação dos relatórios médicos, adicionando¬ lhe anotações semânticas. A informação contida nos relatórios pode desta forma ser publicada na Web, permitindo às máquinas o processamento automático da informação. No entanto, o processo de criação de antologias é bastante complexo, pois existe o problema de criar uma ontologia que não cubra todo o domínio pretendido. Este trabalho incide na criação de uma ontologia e respectiva povoação, através de técnicas de PLN e Aprendizagem Automática que permitem extrair a informação dos relatórios médicos. Foi desenvolvida uma aplicação, que permite ao utilizador converter relatórios do formato digital para o formato OWL. ABSTRACT: Technological evolution has caused a medicine evolution through computer systems which allow storage, gathering and availability of medical information. Medical reports are, most of the times, stored in a non-structured free text and written in a personal way so that misunderstandings may occur. Through Semantic Web languages, it’s possible to use ontology as a way to structure and standardize medical reports information by adding semantic notes. The information in those reports can, by these means, be displayed on the web, allowing machines automatic information processing. However, the process of creating ontology is very complex, as there is a risk creating of an ontology that not covering the whole desired domain. This work is about creation of an ontology and its population through NLP and Machine Learning techniques to extract information from medical reports. An application was developed which allows the user to convert reports from digital for¬ mat to OWL format.
Resumo:
As descrições de produtos turísticos na área da hotelaria, aviação, rent-a-car e pacotes de férias baseiam-se sobretudo em descrições textuais em língua natural muito heterogénea com estilos, apresentações e conteúdos muito diferentes entre si. Uma vez que o sector do turismo é bastante dinâmico e que os seus produtos e ofertas estão constantemente em alteração, o tratamento manual de normalização de toda essa informação não é possível. Neste trabalho construiu-se um protótipo que permite a classificação e extracção automática de informação a partir de descrições de produtos de turismo. Inicialmente a informação é classificada quanto ao tipo. Seguidamente são extraídos os elementos relevantes de cada tipo e gerados objectos facilmente computáveis. Sobre os objectos extraídos, o protótipo com recurso a modelos de textos e imagens gera automaticamente descrições normalizadas e orientadas a um determinado mercado. Esta versatilidade permite um novo conjunto de serviços na promoção e venda dos produtos que seria impossível implementar com a informação original. Este protótipo, embora possa ser aplicado a outros domínios, foi avaliado na normalização da descrição de hotéis. As frases descritivas do hotel são classificadas consoante o seu tipo (Local, Serviços e/ou Equipamento) através de um algoritmo de aprendizagem automática que obtém valores médios de cobertura de 96% e precisão de 72%. A cobertura foi considerada a medida mais importante uma vez que a sua maximização permite que não se percam frases para processamentos posteriores. Este trabalho permitiu também a construção e população de uma base de dados de hotéis que possibilita a pesquisa de hotéis pelas suas características. Esta funcionalidade não seria possível utilizando os conteúdos originais. ABSTRACT: The description of tourism products, like hotel, aviation, rent-a-car and holiday packages, is strongly supported on natural language expressions. Due to the extent of tourism offers and considering the high dynamics in the tourism sector, manual data management is not a reliable or scalable solution. Offer descriptions - in the order of thousands - are structured in different ways, possibly comprising different languages, complementing and/or overlap one another. This work aims at creating a prototype for the automatic classification and extraction of relevant knowledge from tourism-related text expressions. Captured knowledge is represented in a normalized/standard format to enable new services based on this information in order to promote and sale tourism products that would be impossible to implement with the raw information. Although it could be applied to other areas, this prototype was evaluated in the normalization of hotel descriptions. Hotels descriptive sentences are classified according their type (Location, Services and/or Equipment) using a machine learning algorithm. The built setting obtained an average recall of 96% and precision of 72%. Recall considered the most important measure of performance since its maximization allows that sentences were not lost in further processes. As a side product a database of hotels was built and populated with search facilities on its characteristics. This ability would not be possible using the original contents.
Resumo:
The lower crustal structure beneath the Western Alps -- including the Moho -- bears the signature of past and present geodynamic processes. It has been the subject of many studies until now. However, its current knowledge still leaves significant open questions. In order to derive new information, independent from previous determinations, here I wish to address this topic using a different method --- ambient seismic noise autocorrelation --- that is for the first time applied to reveal Moho depth in the Western Alps. Moho reflections are identified by picking reflectivity changes in ambient seismic noise autocorrelations. The seismic data is retrieved from more than 200 broadband seismic stations, from the China--Italy--France Alps (CIFALPS) linear seismic network, and from a subset of the AlpArray Seismic Network (AASN). The automatically-picked reflectivity changes along the CIFALPS transect in the southwestern Alps show the best results in the 0.5--1 Hz frequency band. The autocorrelation reflectivity profile of the CIFALPS transect shows a steeper subduction profile,~55 to ~70 km, of the European Plate underneath the Adriatic Plate. The dense spacing of the CIFALPS network facilitates the detection of lateral continuity of crustal structure, and of the Ivrea mantle wedge reaching shallow crustal depths in the southwestern Alps. The data of the AASN stations are filtered in the 0.4--1 and 0.5--1 Hz frequency bands. Although the majority of the stations give the same Moho depth for the different frequency bands, the few stations with different Moho depths shows the care that has to be taken when choosing the frequency band for filtering the autocorrelation stacks. The new Moho depth maps by using the AASN stations are a compilation of the first and second picked reflectivity changes. The results show the complex crust-mantle structure with clear differences between the northwestern and southwestern Alps.
Resumo:
Sketches are a unique way to communicate: drawing a simple sketch does not require any training, sketches convey information that is hard to describe with words, they are powerful enough to represent almost any concept, and nowadays, it is possible to draw directly from mobile devices. Motivated from the unique characteristics of sketches and fascinated by the human ability to imagine 3D objects from drawings, this thesis focuses on automatically associating geometric information to sketches. The main research directions of the thesis can be summarized as obtaining geometric information from freehand scene sketches to improve 2D sketch-based tasks and investigating Vision-Language models to overcome 3D sketch-based tasks limitations. The first part of the thesis concerns geometric information prediction from scene sketches improving scene sketch to image generation and unlocking new creativity effects. The thesis proceeds showing a study conducted on the Vision-Language models embedding space considering sketches, line renderings and RGB renderings of 3D shape to overcome the use of supervised datasets for 3D sketch-based tasks, that are limited and hard to acquire. Following the obtained observations and results, Vision-Language models are applied to Sketch Based Shape Retrieval without the need of training on supervised datasets. We then analyze the use of Vision-Language models for sketch based 3D reconstruction in an unsupervised manner. In the final chapter we report the results obtained in an additional project carried during the PhD, which has lead to the development of a framework to learn an embedding space of neural networks that can be navigated to get ready-to-use models with desired characteristics.