The data generated from the user's activities and surfing online can have a significant impact when used to improve the content of web pages. The user has little time to scan the content of a web page and the motivation to save time is high. Recommendations and personalized content are becoming more and more common and both businesses and consumers seem to benefit from more targeted content. In order to know what recommendations to present to each individual, information about the user is needed and there are many tools to analyze the behaviours of the users online. In this study, we examined if relevant content on the front-page of Visma, a business software provider, can increase the interaction on the front-page and what metrics can be used to measure the interaction. Together with experts in the field we investigated the eAccounting software users’ preferences for targeted recommendations. By having a pop up survey for users of Visma, conducting an A/B test and using a heatmap for the eAccounting users we found out that a more customized front-page makes the user interact more with the page.

The title page is clearly the main representative of the print media, which often determines their success or failure. An even greater justification for the tabloid newspapers whose everyday existence depends on nonabonent readers. A typical representative of tabloid domestic news is Aha!, which creates his main communicator with no real functioning of the theoretical model. This does not mean that it does not work with repetitive characters or signs in this work to clearly identify key elements for creating and thus the theoretical framework that can be used in practice. To this will serve as an analysis relating to the actual Aha!, so comparisons with by the Lidove noviny and Hospodarske noviny. Researched topic will also be given one of the topical issues related images and text.

The growing popularity of artificial intelligence and machine learning has led to the adop- tion of the automation vision in the industry by many other institutions and organizations. Many corporations have made it their primary objective to make the delivery of goods and services and manufacturing in a more efficient way with minimal human intervention. Au- tomated document processing and analysis is also a critical component of this cycle for many organizations that contribute to the supply chain. The massive volume and diver- sity of data created in this rapidly evolving environment make this a highly desired step. Despite this diversity, important information in the documents is provided in the tables. As a result, extracting tabular data is a crucial aspect of document processing. This thesis applies deep learning methodologies to detect table structure elements for the extraction of data and preparation for semantic modelling. In order to find optimal structure definition, we analyzed the performance of deep learning models in different formats such as row/column and cell. The combined row and column detection models perform poorly compared to other models’ detection performance due to the highly over- lapping nature of rows and columns. Separate row and column detection models seem to achieve the best average F1-score with 78.5% and 79.1%, respectively. However, de- termining cell elements from the row and column detections for semantic modelling is a complicated task due to spanning rows and columns. Considering these facts, a new method is proposed to set the ground-truth information called a content-focused annota- tion to define table elements better. Our content-focused method is competent in handling ambiguities caused by huge white spaces and lack of boundary lines in table structures; hence, it provides higher accuracy. Prior works have addressed the table analysis problem under table detection and table structure detection tasks. However, the impact of dataset structures on table structure detection has not been investigated. We provide a comparison of table structure detection performance with cropped and uncropped datasets. The cropped set consists of only table images that are cropped from documents assuming tables are detected perfectly. The uncropped set consists of regular document images. Experiments show that deep learning models can improve the detection performance by up to 9% in average precision and average recall on the cropped versions. Furthermore, the impact of cropped images is negligible under the Intersection over Union (IoU) values of 50%-70% when compared to the uncropped versions. However, beyond 70% IoU thresholds, cropped datasets provide significantly higher detection performance.

Purpose – The purpose of this thesis is contributing to the research on the efficacy of backlinks originating from Web 2.0 blogs by designing a costless method for creating controllable backlinks to a website, solely with Web 2.0 blogs as a source of backlinks. The objective is to find out if such links can provide an effect on a website’s positions in the Google SERPs in 2020 and to hopefully contribute with a controllable link strategy that is available for any SEO practitioner regardless of their economic circumstances. The thesis provides answers to the two research questions: 1. What positions in the SERPs can an already existing website claim as a result of creating and implementing a link strategy that utilizes Web 2.0 blogs? 2. In context of implementing a link strategy, what practices must be considered for it to remain unpunished by Google in 2020? Method – The choice of research method, due to the nature of the project is Design Science Research (DSR), in which the designed artefact is observationally evaluated by conducting a field study. The artefact consists of four unique Web 2.0 blogs that each sent a backlink to the target website through qualitative blog posts following Google’s guidelines. Quantitative data was collected using SERPWatcher by Mangools, which tracked 29 keywords for 52 days, and was qualitatively analysed. Conclusions – There is a distinct relation between the improvement in keyword positions and the implementation of the artefact, leaving us with the conclusion that it is reasonable to believe that Web 2.0 blog backlinks can affect a website’s positions in the SERPs in the modern Google Search. More research experimenting with Web 2.0 blogs as the origin of backlinks must be conducted in order to truly affirm or deny this claim, as an evaluation on solely one website is insufficient. It can be concluded that the target website was not punished by Google after implementation. While their search algorithm may be complex and intelligent, it was not intelligent enough to punish our intentions of manipulating another website’s keyword positions via a link scheme. Passing through as legitimate may have been due to following E-A-T practices and acting natural, but this is mere speculation without comparisons with similar strategies that disregard these practices. Limitations – Rigorous testing and evaluation of the designed artefact and its components is very important when conducting research that employs DSR as a method. Due to time constraints, the lack of data points in form of websites the artefact has been tested on, as well as the absence of iterative design, partially denies the validity of the artefact since it does not meet the criteria of being rigorously tested. The data collected would be more impactful if keyword data were gathered many days before executing the artefact, as a pre-implementation period larger than 7 days would act as a reference point when evaluating the effect. It would also be ideal to track the effects post-implementation for a longer time period due to the slow nature of SEO. Keywords – SEO, search engine optimization, off-page optimization, Google Search, Web 2.0, backlinks.

This thesis deals with the design and implementation of the page layout manager for a web user interface composed of components. A part of solution is also a new XML format for configuring of the manager of page layout and composition and a new application interface for components. The created system has met the requirements of the European project KiWi and has passed the acceptance tests of its project team.

This project is interested in creating application for generating dynamic web pages which are connected to database. Main intention of this project is concentrated to set out basic parts and create class diagram of this application. Final application will be used for simplification of web pages design for non-IT users. Final application represents concept for any extension and modification in the future.

Získávání informací a jiné techniky dolování dat z webových stránek získávají na důležitosti s tím, jak se rozvíjí webové technologie a jak roste množství informací uložených na webu, jakožto jediném nosiči těchto informací. Spolu s tímto množství informací také ale roste množství obsahu, který není v kontextu prezentovaných informací ničím důležitý. To je jedním z důvodů, proč je důležité se intenzivně věnovat předzpracování informací uložených na webu. Segmentační algoritmy jsou jedním z možných způsobů předzpracování. Tato práce se věnuje využití shlukovacích technik pro zefektivnění existujících, ale i nalezení zcela nových algoritmů použitelných pro segmentaci webových stránek.

This thesis examines Fielding Burke's Call Home the Heart, Grace Lumpkin's To Make My Bread, and Myra Page's Gathering Storm through the lens of ecofeminism, an interdisciplinary theory that contributes the necessary insight into the link between the abuse of power on personal, political, and economic levels that underlies the human oppression and environmental exploitation experienced by the novels' characters and communities. A resurrection of the Gastonia novels through the framework of ecofeminism will contribute to the scholarly discourse regarding this maturing theory as well as intensify the critical body of work concerning the Gastonia novels themselves. This thesis, in conjunction with the works of instrumental Appalachian scholars, literary critics, and historians as well as major landmark texts in the field of ecofeminism such as Kathy Warren's Ecofeminism: Women, Culture, Nature and Greta Gaard's Ecofeminism: Women, Animals, Nature, purposes to advance the critical standing of the Gastonia novels.

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