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Supporting Structured Browsing for Full-Text Scientific Research Reports  [PDF]
Robert B. Allen
Computer Science , 2012,
Abstract: Scientific research is highly structured and some of that structure is reflected in research reports. Traditional scientific research reports are yielding to interactive documents which expose their internal structure and are richly linked to other materials. In these changes, there are opportunities to take advantage of the structure in scientific research reports which previously have not been systematically captured. Thus, we explore ways of capturing more of the structure of research in reports about the research and we use that structure to support the development of a new generation of document browsers which include novel interaction widgets. We apply the browsers incorporating the conceptual modeling framework to full-text research reports from the Public Library of Science (PLoS). In addition, we describe the application of model-oriented constructs to facilitating highly interlinked digital libraries.
Extraction of Radiology Reports using Text mining
A.V.Krishna Prasad,Dr.S.Ramakrishna,Dr.D.Sravan Kumar,Dr.B.Padmaja Rani
International Journal on Computer Science and Engineering , 2010,
Abstract: In this paper, we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: medical finding extractor, report and image retriever. The medical finding extraction module automatically extracts medical findings and associated modifiers to structure radiology reports. The structuring of the free text reports bridges the gap between users and report database, makes the information contained in the reports readily accessible. It also serves as intermediate result to other components of the system. The retrieval module analyzes user’s query and returns the reports and images that match the query. The overallevaluation results are satisfactory, though more thorough testing and evaluation are needed. Our future work includes improving the current system performance and implementing the radiology report generation system using statistical machine translation approach, for which we have designed the general architecture.
Deep Structured Output Learning for Unconstrained Text Recognition  [PDF]
Max Jaderberg,Karen Simonyan,Andrea Vedaldi,Andrew Zisserman
Computer Science , 2014,
Abstract: We develop a representation suitable for the unconstrained recognition of words in natural images: the general case of no fixed lexicon and unknown length. To this end we propose a convolutional neural network (CNN) based architecture which incorporates a Conditional Random Field (CRF) graphical model, taking the whole word image as a single input. The unaries of the CRF are provided by a CNN that predicts characters at each position of the output, while higher order terms are provided by another CNN that detects the presence of N-grams. We show that this entire model (CRF, character predictor, N-gram predictor) can be jointly optimised by back-propagating the structured output loss, essentially requiring the system to perform multi-task learning, and training uses purely synthetically generated data. The resulting model is a more accurate system on standard real-world text recognition benchmarks than character prediction alone, setting a benchmark for systems that have not been trained on a particular lexicon. In addition, our model achieves state-of-the-art accuracy in lexicon-constrained scenarios, without being specifically modelled for constrained recognition. To test the generalisation of our model, we also perform experiments with random alpha-numeric strings to evaluate the method when no visual language model is applicable.
A semi-structured document model for text mining
A Semi-Structured Document Model for Text Mining

Yang Jianwu,and Chen Xiaoou,

计算机科学技术学报 , 2002,
Abstract: A semi-structured document has more structured information compared to an ordinary document, and the relation among semi-structured documents can be fully utilized. In order to take advantage of the structure and link information in a semi-structured document for better mining, a structured link vector model (SLVM) is presented in this paper, where a vector represents a document, and vectors' elements are determined by terms, document structure and neighboring documents. Text mining based on SLVM is described in the procedure of K-means for briefness and clarity: calculating document similarity and calculating cluster center. The clustering based on SLVM performs significantly better than that based on a conventional vector space model in the experiments, and its F value increases from 0.65-0.73 to 0.82-0.86.
Age-Structured Epidemic Model for Transmission Dynamics of Tuberculosis
Umar Mallam Abdulkarim
Research Journal of Applied Sciences , 2012,
Abstract: We proposed an age structured transmission dynamics model for the transmission of Tuberculosis, along the line of the classical Mckendrick-Foerster, age-structured population models based on some assumptions contrary to the Castillo-Chavez assumptions of age depended mortality rate and age depended contact rate, vaccination and treatment rates of the infected. Rather, our model assumes constant contact rate, no vaccination and treatment, infectives are removed and quarantine till non- disease induced death. We then examined the existence of non trivial steady states of the model and discussed their stability via the basic reproductive number of the disease. Also the equations for the population compartments are obtained.
Modeling Horizontal Transmission of HIV/AIDS in an Age-Structured Population
M.A. Umar,O.E. Olowofeso,R.A. Ademiluyi
Journal of Modern Mathematics and Statistics , 2012,
Abstract: We extended McKendrick-Von-Foerster type age-structured model to formulate a 2-age groups structured for heterosexual transmission of HIV/AIDS, in a proportionate mixing population, with constant per capital force of infection. We derive the governing equations, which describes the dynamics of population and examine the model for local stability of the endemic state. We found that to get a disease-free state we need to maximize the transfer rate between the sexually immature group and sexually matured group and minimize the average time spend as infective in group 2, before developing AIDS.
Combining Free Text and Structured Electronic Medical Record Entries to Detect Acute Respiratory Infections  [PDF]
Sylvain DeLisle,Brett South,Jill A. Anthony,Ericka Kalp,Adi Gundlapallli,Frank C. Curriero,Greg E. Glass,Matthew Samore,Trish M. Perl
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0013377
Abstract: The electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).
Behavioral Modernity and the Cultural Transmission of Structured Information: The Semantic Axelrod Model  [PDF]
Mark E. Madsen,Carl P. Lipo
Quantitative Biology , 2014,
Abstract: Cultural transmission models are coming to the fore in explaining increases in the Paleolithic toolkit richness and diversity. During the later Paleolithic, technologies increase not only in terms of diversity but also in their complexity and interdependence. As Mesoudi and O'Brien (2008) have shown, selection broadly favors social learning of information that is hierarchical and structured, and multiple studies have demonstrated that teaching within a social learning environment can increase fitness. We believe that teaching also provides the scaffolding for transmission of more complex cultural traits. Here, we introduce an extension of the Axelrod (1997} model of cultural differentiation in which traits have prerequisite relationships, and where social learning is dependent upon the ordering of those prerequisites. We examine the resulting structure of cultural repertoires as learning environments range from largely unstructured imitation, to structured teaching of necessary prerequisites, and we find that in combination with individual learning and innovation, high probabilities of teaching prerequisites leads to richer cultural repertoires. Our results point to ways in which we can build more comprehensive explanations of the archaeological record of the Paleolithic as well as other cases of technological change.
Data Mining of Causal Relations from Text: Analysing Maritime Accident Investigation Reports  [PDF]
Santosh Tirunagari
Computer Science , 2015,
Abstract: Text mining is a process of extracting information of interest from text. Such a method includes techniques from various areas such as Information Retrieval (IR), Natural Language Processing (NLP), and Information Extraction (IE). In this study, text mining methods are applied to extract causal relations from maritime accident investigation reports collected from the Marine Accident Investigation Branch (MAIB). These causal relations provide information on various mechanisms behind accidents, including human and organizational factors relating to the accident. The objective of this study is to facilitate the analysis of the maritime accident investigation reports, by means of extracting contributory causes with more feasibility. A careful investigation of contributory causes from the reports provide opportunity to improve safety in future. Two methods have been employed in this study to extract the causal relations. They are 1) Pattern classification method and 2) Connectives method. The earlier one uses naive Bayes and Support Vector Machines (SVM) as classifiers. The latter simply searches for the words connecting cause and effect in sentences. The causal patterns extracted using these two methods are compared to the manual (human expert) extraction. The pattern classification method showed a fair and sensible performance with F-measure(average) = 65% when compared to connectives method with F-measure(average) = 58%. This study is an evidence, that text mining methods could be employed in extracting causal relations from marine accident investigation reports.
Age-Structured Transmission Dynamics Model for Vertical and Horizontal Transmission of HIV/AIDS
M.A. Umar,E.O. Olowofeso,R.A. Ademiluyi
Journal of Modern Mathematics and Statistics , 2012,
Abstract: Transmission dynamics model for HIV/AIDS, along the line of Mckendrick-Forester age-structured model is proposed with the natural mortality rate and the fertility functions assumed to be age depended, similar to Doma, Gurtin-MacCamy definitions. The solutions to the governing equations are obtained and the steady states are examined for their local stability. The model is further extended to study the case of constant mortality rate and an exponential type of interaction function. It is observed that the endemic steady exist and asymptotically stable.
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