Martina Zachariasova, Patrik Kamencay, Robert Hudec, Miroslav Benco, Slavomir Matuska
{"title":"A Novel Imaging Approach of Web Documents based on Semantic Inclusion of Textual and Non – Textual Information","authors":"Martina Zachariasova, Patrik Kamencay, Robert Hudec, Miroslav Benco, Slavomir Matuska","doi":"10.1016/j.aasri.2014.09.007","DOIUrl":null,"url":null,"abstract":"<div><p>This paper deals with research in the area of a novel imaging approach of web documents based on semantic inclusion of textual and non-textual informations. The main idea was to create a robust method for relevant display results into search engine based on search by keywords or images. Thus, we proposed method called Semantic Inclusion of Images and Textual (SIIT) segments. The output SIIT method is short web document. It contains image and textual segments, which are semantic linked. Creation of short web document to possible three steps was divided. Firstly, the all images and textual segments from main content web document were extracted. Secondly, extraction images were analyzed in order to obtain of semantic description objects into image. Finally, linked images and textual segments using linguistic analysis.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"9 ","pages":"Pages 31-36"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2014.09.007","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AASRI Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212671614001073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper deals with research in the area of a novel imaging approach of web documents based on semantic inclusion of textual and non-textual informations. The main idea was to create a robust method for relevant display results into search engine based on search by keywords or images. Thus, we proposed method called Semantic Inclusion of Images and Textual (SIIT) segments. The output SIIT method is short web document. It contains image and textual segments, which are semantic linked. Creation of short web document to possible three steps was divided. Firstly, the all images and textual segments from main content web document were extracted. Secondly, extraction images were analyzed in order to obtain of semantic description objects into image. Finally, linked images and textual segments using linguistic analysis.
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