Reflowable Document Images for the Web
نویسنده
چکیده
The paper describes on-going work on a system that transforms page-oriented document images into “reflowable document images”, representations of the page image in HTML format that allows it to adapt to display devices of different sizes while preserving the original appearance of the image as much as possible and avoiding OCR errors. The approach to document layout analysis used by the system is outlined and the strengths and limitations of HTML for this application are discussed.
منابع مشابه
An Ensemble Click Model for Web Document Ranking
Annually, web search engine providers spend more and more money on documents ranking in search engines result pages (SERP). Click models provide advantageous information for ranking documents in SERPs through modeling interactions among users and search engines. Here, three modules are employed to create a hybrid click model; the first module is a PGM-based click model, the second module in a d...
متن کاملرفع اعوجاج هندسی متون بهکمک اطلاعات هندسی خطوط متن
Document images produced by scanners or digital cameras usually have photometric and geometric distortions. If either of these effects distorts document, recognition of words from such a document image using OCR is subject to errors. In this paper we propose a novel approach to significantly remove geometric distortion from document images. In this method first we extract document lines from do...
متن کاملRRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features
Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking algorithm using reinforcement learning. The proposed algorithm is called RRLUFF, in which the rank...
متن کاملLearning Document Image Features With SqueezeNet Convolutional Neural Network
The classification of various document images is considered an important step towards building a modern digital library or office automation system. Convolutional Neural Network (CNN) classifiers trained with backpropagation are considered to be the current state of the art model for this task. However, there are two major drawbacks for these classifiers: the huge computational power demand for...
متن کاملHierarchical Fuzzy Clustering Semantics (HFCS) in Web Document for Discovering Latent Semantics
This paper discusses about the future of the World Wide Web development, called Semantic Web. Undoubtedly, Web service is one of the most important services on the Internet, which has had the greatest impact on the generalization of the Internet in human societies. Internet penetration has been an effective factor in growth of the volume of information on the Web. The massive growth of informat...
متن کامل