A semi-automated framework for semantically annotating web content

Abdou, Mohamed; AbdelGaber, Sayed; Salah, Mona

doi:10.1016/j.future.2017.11.008

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Due to the limited marketing field of the static site and, accordingly, the inability to place all the necessary elements of the semantic core on the main page and in the description of the goods or services, the adequate solution is to create the dynamic sections. The blog or news can be updated quite often; the amount of the text available to the developer is expanded, so the grouping of the semantic core involves the allocation of a group of information requests, through which pages with relevant articles are promoted [9].…”

Section: Resultsmentioning

confidence: 99%

Towards Question on Linguistic Approach to Search Engine Optimization: Clustering, Collocation, Grams

et al. 2018

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The article is devoted to the problem of search engine optimization in the context of nowadays reality. Linguistics can become one of the main instruments to improve its marketing position of the web-product so the linguistic approach to the search engine optimization acts as the modern and effective mechanism. The task of search engine optimization is to achieve the most effective promotion of the site in the search engines while preserving the most possible naturalness of the text. Now the topic of the so-called over-optimized texts is becoming especially urgent. One of the ways of the search engine optimization of a site can be clustering as an automatic search and detection of semantically similar groups of files among a predetermined number of files. Also the method of collocations is an extremely topical linguistic method for solving problems of search optimization. Philological science also offers the developers a method close to the method of collocations - sthe gram-method. The linguistic approach to search engine optimization obviously allows us not only to increase the effectiveness of SEO in terms of the results obtained, but also to facilitate and accelerate the development processes and ultimately the business processes.

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Section: Resultsmentioning

confidence: 99%

Towards Question on Linguistic Approach to Search Engine Optimization: Clustering, Collocation, Grams

et al. 2018

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“…Content structure Editing of articles; category descriptions; offers; or products [61] Website structure Modification of navigation elements; internal linking [62]; structured data [63] Technical layer The speed at which a webpage is displayed in a browser [64]; the speed of downloading content by web robots; SSL encryption [65]; adaptation to mobile devices User experience and trust Adaptation of the site in accordance with the WCAG standard [66]; clarity and originality of content; number and placement of ads…”

Section: Element Descriptionmentioning

confidence: 99%

From Web Catalogs to Google: A Retrospective Study of Web Search Engines Sustainable Development

2023

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This study presents a review of search engines and search engine optimization and shows how the search engine landscape relates to sustainable development. We have used a narrative review research method and described three main topics: the past and present of web catalogs and search engines; current knowledge about the dominant types of search results presented in Google search; and methods of search engine optimization. Technical elements of important website areas related to technical website auditing are discussed. We summarize our research with several key findings on how web search engines are involved in sustainable development and offer a glimpse into the future use of web searching with the help of artificial intelligence chats and prompt engineering.

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“…Overall, annotations can be assimilated to metadata associated with particular text extracts from a document or any other pieces of information. Semantic annotation helps deal with natural language ambiguity and its representation through ontologies [84,85]. This process involves relating text extracts with tags representing ontological elements (concepts, relations, attributes, and instances), which enables document processing by software systems.…”

Section: Language Technologies For Knowledge Acquisitionmentioning

confidence: 99%

Knowledge-Based System for Crop Pests and Diseases Recognition

2021

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With the rapid increase in the world’s population, there is an ever-growing need for a sustainable food supply. Agriculture is one of the pillars for worldwide food provisioning, with fruits and vegetables being essential for a healthy diet. However, in the last few years the worldwide dispersion of virulent plant pests and diseases has caused significant decreases in the yield and quality of crops, in particular fruit, cereal and vegetables. Climate change and the intensification of global trade flows further accentuate the issue. Integrated Pest Management (IPM) is an approach to pest control that aims at maintaining pest insects at tolerable levels, keeping pest populations below an economic injury level. Under these circumstances, the early identification of pests and diseases becomes crucial. In this work, we present the first step towards a fully fledged, semantically enhanced decision support system for IPM. The ultimate goal is to build a complete agricultural knowledge base by gathering data from multiple, heterogeneous sources and to develop a system to assist farmers in decision making concerning the control of pests and diseases. The pest classifier framework has been evaluated in a simulated environment, obtaining an aggregated accuracy of 98.8%.

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A semi-automated framework for semantically annotating web content

Cited by 3 publications

References 6 publications

Towards Question on Linguistic Approach to Search Engine Optimization: Clustering, Collocation, Grams

Towards Question on Linguistic Approach to Search Engine Optimization: Clustering, Collocation, Grams

From Web Catalogs to Google: A Retrospective Study of Web Search Engines Sustainable Development

Knowledge-Based System for Crop Pests and Diseases Recognition

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