Graphical Contents and Health Websites Readability

Health-related websites provide valuable information, resources, and support for individuals seeking to improve their health and make informed decisions about their well-being. Graphical content makes websites visually appealing and helps create a positive first impression. Relevant and high-quality graphical content can immediately capture visitors attention and make the website more attractive and memorable. However, irrelevant graphical content on web pages also indicates poor readability, distracting readers from the texts focus. This papers primary objective is to assess the effect of irrelevant or low-quality graphical content on the readability of a health-related website. The relevance of graphical content on a website was computed using a tool proposed in our previous research. A user study comprised of end-user evaluation and heuristic evaluation by readability experts was conducted using a variety of question categories. Both evaluation methods yielded comparable results, confirming that the pertinent graphical content enhances the readability of the web page

Análisis de relaciones cienciométricas y lingüísticas en un entorno automatizado

Se presenta una visión integradora de las diferentes herramientas que permiten el estudio de las conexiones entre documentos, las pautas de publicación, la representación del contenido y la optimización de la recuperación. Se entremezclan conceptos de Psicología Cognitiva,Lingüística, Cienciometría, Documentación, Estadística, Clasificación e Informática en sus vertientes más relacionadas con el tratamiento, organización y caracterización de información textual. El objetivo final es analizar la influencia que tiene el análisis de género en la carcterización de los parámetros cualitativos y cuantitativos, y en concreto, de las herramientas que se encargan tradicionalmente de estos estudios, como los indicadores cienciométricos y la clasificación de término

Readability of Non-text Images on the World Wide Web (WWW)

The World Wide Web associated the world in a manner that was unrealistic previously and made it a lot more straightforward for users to get data, share and impart. But, irrelevant non-text images on the web pages equally specify poor readability, disrupting the people from the emphasis of the reading. The main goal of this paper is to evaluate the impact of irrelevant or low-quality non-text images on the readability of the webpage. An automatic methodology has been proposed to compute the relevancy of the non-text images. This methodology merges different approaches to extract information from non-text images and read text from websites in order to find relevancy between them. This technique was used to analyze fifty different educational websites to automatically find the relevancy of their non-text images. A user study has been carried out to evaluate the proposed methodology with different types of questions. The results agree with the fact that the relevant non-text images enhance the readability of the web page. This research work will help web designers to improve readability by considering only the relevant content of a web page, without relying on expert judgment.This work was supported in part by the Spanish Ministry of Economy, Industry and Competitiveness under Grant CSO2017-86747-R, in part by the Andalusia Regional Projects under Grant AT17-5509-UMA ``ROSI'' and Grant UMA18-FEDERJA-074 ``ITERA,'' and in part by the European art83 under Contract 8.06/5.58.5900 DIH-HERO ``SUSTAIN.'

Text Summarization Technique for Punjabi Language Using Neural Networks

In the contemporary world, utilization of digital content has risen exponentially. For example, newspaper and web articles, status updates, advertisements etc. have become an integral part of our daily routine. Thus, there is a need to build an automated system to summarize such large documents of text in order to save time and effort. Although, there are summarizers for languages such as English since the work has started in the 1950s and at present has led it up to a matured stage but there are several languages that still need special attention such as Punjabi language. The Punjabi language is highly rich in morphological structure as compared to English and other foreign languages. In this work, we provide three phase extractive summarization methodology using neural networks. It induces compendious summary of Punjabi single text document. The methodology incorporates pre-processing phase that cleans the text; processing phase that extracts statistical and linguistic features; and classification phase. The classification based neural network applies an activation function- sigmoid and weighted error reduction-gradient descent optimization to generate the resultant output summary. The proposed summarization system is applied over monolingual Punjabi text corpus from Indian languages corpora initiative phase-II. The precision, recall and F-measure are achieved as 90.0%, 89.28% an 89.65% respectively which is reasonably good in comparison to the performance of other existing Indian languages" summarizers.This research is partially funded by the Ministry of Economy, Industry and Competitiveness, Spain (CSO2017-86747-R)

Indexing Languages for Information Management, a Promising Future or an Obsolete Resource?

Indexing languages have traditionally been an essential tool for organizing and retrieving documental information. The inclusion of indexing languages into the digital environment leads to new frontiers, but also new opportunities. This study shows the historical evolution of the indexing languages and its application in document management field. We analyze diverse trends for their digital use from two perspectives: their integration with other digital and linguistic resources, and the adjustment of them into the Web environment. Finally, there is an analysis of how these languages are used in the Web 2.0 and the incorporation of ontologies in the Semantic Web.This work was carried out within the framework of a research Project financed by the Spanish government (Ministerio de Educación y Ciencia, Secretaría de Estado de Universidades e Investigación, TIN 2007-67153)

Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm

In the present scenario, Automatic Text Summarization (ATS) is in great demand to address the ever-growing volume of text data available online to discover relevant information faster. In this research, the ATS methodology is proposed for the Hindi language using Real Coded Genetic Algorithm (RCGA) over the health corpus, available in the Kaggle dataset. The methodology comprises five phases: preprocessing, feature extraction, processing, sentence ranking, and summary generation. Rigorous experimentation on varied feature sets is performed where distinguishing features, namely- sentence similarity and named entity features are combined with others for computing the evaluation metrics. The top 14 feature combinations are evaluated through Recall-Oriented Understudy for Gisting Evaluation (ROUGE) measure. RCGA computes appropriate feature weights through strings of features, chromosomes selection, and reproduction operators: Simulating Binary Crossover and Polynomial Mutation. To extract the highest scored sentences as the corpus summary, different compression rates are tested. In comparison with existing summarization tools, the ATS extractive method gives a summary reduction of 65%

Factores económicos y políticos en la brecha digital

Ponencias de la Segunda Conferencia internacional sobre brecha digital e inclusión social, celebrada del 28 al 30 de octubre de 2009 en la Universidad Carlos III de MadridLa Web, durante muchos años, se ha perfilado como una solución para eliminar fronteras en la brecha digital. Algunas de las propuestas han sido aplicaciones como el acceso a la información por buscadores, traductores automáticos online gratuitos; ordenadores para el Tercer Mundo como el proyecto promovido por Negroponte desde el MIT ; el acceso abierto a materiales docentes como el OCW y a contenido como la Wikipedia o el desarrollo de software libre . En paralelo, se observa la aparición de factores no previstos en la propuesta inicial y que tienden a ampliar la brecha digital. A través de la Unión Europea se crea Quaero en 2006. Quaero se presenta como el buscador europeo que compita contra Google para eliminar el sesgo idiomático del buscador estadounidense. Otro aspecto es la falta de usabilidad de la futura Web Semántica que parece también crear una nueva frontera. Dentro de las más inquietantes, y menos referenciadas, se encuentra la manipulación económica y política de los recursos. En esta ponencia se hablará sobre su naturaleza y alguna de sus causas

Evolution of web positioning factors and adaptation of optimization tools

Las herramientas de optimización web, Search Engine Optimization (SEO), se utilizan para analizar y mejorar los sitios web en relación a distintos factores de posicionamiento. Esta investigación estudia la evolución de las estrate- gias de posicionamiento web y analiza la adaptación de las herramientas de optimización a estos factores. Además, se estudian qué factores de posicionamiento están presentes en las herramientas SEO más populares. En la fase experimen- tal se analiza el grado en que las estrategias de optimización mejoran el posicionamiento, y en qué medida se encuentran esas funcionalidades en las herramientas SEO. Adicionalmente se han analizado foros y blogs oficiales para descubrir nuevas pautas de evolución de los motores de búsqueda y el grado en que las herramientas SEO pueden adaptarse a dichos cambios. Aunque estas herramientas optimizan el posicionamiento, los resultados sugieren la necesidad de intro- ducir importantes mejoras que aumenten su potencialidad futura.Search Engine Optimization (SEO) tools are designed to analyze and optimize resources regarding positioning factors. Web positioning techniques are applied in order to improve the relevancy of web resources. Webmasters usually use SEO tools to analyze a web site according to some positioning factor. They are required to be updated to achieve two basic goals: to increase the user’s satisfaction while searching the web and to decrease web spamming. We have studied the trends that affect positioning algorithms and optimization techniques. Several SEO tools were analysed in order to learn which functionalities have been implemented. Furthermore, an experiment was performed to test how the positioning factors help optimize the results and if these factors are present in the functionalities found in the SEO tools. Finally, a literature review was carried out to detect future trends in search engines’ algorithms. Results show that SEO tools help in the optimization process but to an insufficient degree; therefore the algorithm’s evolution study suggests that there is a need for major updates in the short ter

Automated Readability Assessment for Spanish e-Government Information

This paper automatically evaluates the readability of Spanish e-government websites. Specifically, the websites collected explain e-government administrative procedures. The evaluation is carried out through the analysis of different linguistic characteristics that are presumably associated with a better understanding of these resources. To this end, texts from websites outside the government websites have been collected. These texts clarify the procedures published on the Spanish Government"s websites. These websites constitute the part of the corpus considered as the set of easy documents. The rest of the corpus has been completed with counterpart documents from government websites. The text of the documents has been processed, and the difficulty is evaluated through different classic readability metrics. At a later stage, automatic learning methods are used to apply algorithms to predict the difficulty of the text. The results of the study show that government web pages show high values for comprehension difficulty. This work proposes a new Spanish-language corpus of official e-government websites. In addition, a large number of combined linguistic attributes are applied, which improve the identification of the level of comprehensibility of a text with respect to classic metrics.Work supported by the Spanish Ministry of Economy, Industry and Competitiveness, (CSO2017-86747-R)