一种基于文本和非文本信息语义包含的Web文档成像新方法

AASRI Procedia Pub Date : 2014-01-01 DOI:10.1016/j.aasri.2014.09.007

Martina Zachariasova, Patrik Kamencay, Robert Hudec, Miroslav Benco, Slavomir Matuska

{"title":"一种基于文本和非文本信息语义包含的Web文档成像新方法","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":"{\"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}","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

摘要

本文研究了一种新的基于文本和非文本信息语义包含的web文档成像方法。其主要思想是创建一种健壮的方法，将相关的显示结果显示到基于关键词或图像的搜索引擎中。因此，我们提出了图像和文本片段的语义包含(SIIT)方法。输出SIIT方法是一个简短的web文档。它包含图像和文本片段，它们是语义链接的。将创建短web文档分为可能的三个步骤。首先，从主要内容web文档中提取所有图像和文本片段;其次，对提取图像进行分析，获得图像中语义描述对象;最后，使用语言分析将图像和文本片段链接起来。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

A Novel Imaging Approach of Web Documents based on Semantic Inclusion of Textual and Non – Textual Information

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助