Achieving scientific document retrieval by considering the wealth of mathematical expressions and the semantic text they contain has become an inescapable trend. Current scientific document matching models focus solely on the textual features of expr...
Traditional mathematical search models retrieve scientific documents only by mathematical expressions and their contexts and do not consider the ontological attributes of scientific documents, which result in gaps between the queries and the retrieva...
Most digital libraries that provide user-friendly interfaces, enabling quick and intuitive access to their resources, are based on Document Image Analysis and Recognition (DIAR) methods. Such DIAR methods need ground-truthed document images to be eva...
Electronic documents are becoming increasingly popular in various industries and sectors as they provide greater convenience and cost-efficiency than physical documents. PDF is a widely used format for creating and sharing electronic documents, while...
Document image enhancement methods are often used to improve the accuracy and efficiency of automated document analysis and recognition tasks such as character recognition. These document images could be degraded or damaged for various reasons includ...
Organisations heavily dependent on paper documents still spend a significant amount of time managing a large volume of documents. An intelligent document management system (DMS) is presented to automate the processing of tax and administrative docume...
Digital document communication between an enterprise and a customer is becoming a primary form of communication rather than the traditional physical document communication. A PDF document, the most popular document format, provides an identical docum...
Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the...
Analyses the concept of document, using as theoretical support, discussions created by authors from the library and Information Science mainly from France and United States traditions. Discussions about information philosophy based on the works of Ra...
Various government and commercial services, including, but not limited to, e-government, fintech, banking, and sharing economy services, widely use smartphones to simplify service access and user authorization. Many organizations involved in these ar...
Fluid office documents, as semi-structured data often represented by Extensible Markup Language (XML) are important parts of Big Data. These office documents have different formats, and their matching Application Programming Interfaces (APIs) depend...
The efficiency of information retrieval systems primarily depends on the effective representation of documents during query processing. This representation is mainly constructed from relevant document terms identified and selected during their indexi...
Social Media, Web Portals and, in general, information systems offer their own Application Programming Interfaces (APIs), used to provide large data sets concerning every aspect of day-by-day life. APIs usually provide data sets as collections of JSO...
Slanted text has been demonstrated to be a salient feature of handwriting. Its estimation is a necessary preprocessing task in many document image processing systems in order to improve the required training. This paper describes and evaluates a new...
In this article, we describe a new formalized method for constructing the NoSQL document database of MongoDB, taking into account the structure of queries planned for execution to the database. The method is based on set theory. The initial data are...
In a multi-document summarization task, if the user can decide on the summary topic, the generated summary can better align with the reader’s specific needs and preferences. This paper addresses the issue of overly general content generation by...
In today’s digital age, the conversion of hardcopy documents into digital formats is widespread. This process involves electronically scanning and storing large volumes of documents. These documents come from various sources, including records...
Applications for document similarity detection are widespread in diverse communities, including institutions and corporations. However, currently available detection systems fail to take into account the private nature of material or documents that h...
Understanding document layouts is vital for enhancing document exploration and information retrieval for sighted individuals. However, for blind and visually impaired people, it becomes challenging to have access to layout information using typical a...
List intersection plays a pivotal role in various domains such as search engines, database systems, and social networks. Efficient indexes and query strategies can significantly enhance the efficiency of list intersection. Existing inverted index-bas...
Optical Character Recognition (OCR) is an indispensable tool for technology users nowadays, as our natural language is presented through text. We live under the need of having information at hand in every circumstance and, at the same time, having ma...
Portable digital devices such as PDAs and camera phones are the easiest and most widely used methods to preserve and collect information. Capturing a document image using this method always has warping issues, especially when capturing pages from a b...
In many countries, document and border procedures create trading barriers, thereby impairing economic growth. These can range from insufficient transshipment facilities to unsupportive institutional arrangements. To address this, countries have taken...
The intrinsic features of documents, such as paper color, texture, aging, translucency, the kind of printing, typing or handwriting, etc., are important with regard to how to process and enhance their image. Image binarization is the process of produ...
Mutual information is one of the mostly used measures for evaluating image similarity. In this paper, we investigate the application of three different Tsallis-based generalizations of mutual information to analyze the similarity between scanned docu...
Document scanning often suffers from skewing, which may seriously influence the efficiency of Optical Character Recognition (OCR). Therefore, it is necessary to correct the skewed document before document image information analysis. In this article,...
We propose a fast document image thresholding method (FADIT) and evaluations of the two classic methods for demonstrating the effectiveness of FADIT. We put forward two assumptions: (1) the probability of the occurrence of grayscale text and backgrou...
Extractive summarization aims to produce a concise version of a document by extracting information-rich sentences from the original texts. The graph-based model is an effective and efficient approach to rank sentences since it is simple and easy to u...
Document authentication remains a pressing challenge in various domains, including financial services, academic credentialing, healthcare, and supply chain management. Existing centralized verification systems are vulnerable to manipulation, ineffici...
The digitization of paper documents enables rapid sharing and long-term preservation of information, making it a widely adopted approach for efficient document storage and management across various domains. However, the recent advances in image editi...
Current state-of-the-art neural machine translation (NMT) architectures usually do not take document-level context into account. However, the document-level context of a source sentence to be translated could encode valuable information to guide the...
Preprocessing is one of the main components in a conventional document categorization (DC) framework. This paper aims to highlight the effect of preprocessing tasks on the efficiency of the Arabic DC system. In this study, three classification techni...
Table detection in document images is a challenging problem due to diverse layouts, irregular structures, and embedded graphical elements. In this study, we present HTTD (Hierarchical Transformer for Table Detection), a cutting-edge model that combin...
In this paper, we describe our biomedical document retrieval system and answers extraction module, which is part of the biomedical question answering system. Approximately 26.5 million PubMed articles are indexed as a corpus with the Apache Lucene te...
Nowadays, deep learning methods are employed in a broad range of research fields. The analysis and recognition of historical documents, as we survey in this work, is not an exception. Our study analyzes the papers published in the last few years on t...
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Digital watermarking is a promising technology to embed information as unperceivable signals in digital contents. Various watermarking techniques have been proposed to protect copyrights of multimedia digital contents over Internet trading so that ow...
In this paper we perform a comparative analysis of three models for a feature representation of text documents in the context of document classification. In particular, we consider the most often used family of bag-of-words models, the recently propo...
Hyperspectral data analysis is being utilized as an effective and compelling tool for image processing, providing unprecedented levels of information and insights for various applications. In this manuscript, we have compiled and presented a comprehe...
Aiming at the common problems of intelligent document platform-dependency, this paper proposes an MVC-based (Model View Controller-based) intelligent document model using UIML (User Interface Markup Language). The model is made on the basis of the pr...
Tables in document images are an important entity since they contain crucial information. Therefore, accurate table detection can significantly improve the information extraction from documents. In this work, we present a novel end-to-end trainable p...
Data can be represented in many different ways within a particular document or set of documents. Hence, attempts to automatically process the relationships between documents or determine the relevance of certain document objects can be problematic. I...
Previous researchers have considered sentiment analysis as a document classification task, in which input documents are classified into predefined sentiment classes. Although there are sentences in a document that support important evidences for sent...
The patent document has different content for each paragraph, and the length of the document is also very long. Moreover, patent documents are classified hierarchically as multi-labels. Many works have employed deep neural architectures to classify t...
Question answering from visually rich documents (VRDs) is the task of retrieving the correct answer to a natural language question by considering the content of textual and visual elements in the document, as well as the pages’ layout. To answe...
Regardless of revolutionizing improvements in various domains thanks to recent advancements in the field of Deep Learning (DL), recent studies have demonstrated that DL networks are susceptible to adversarial attacks. Such attacks are crucial in sens...
Document-level Sentiment Analysis is a complex task that implies the analysis of large textual content that can incorporate multiple contradictory polarities at the phrase and word levels. Most of the current approaches either represent textual data...
Currently, as an effect of the COVID-19 pandemic, bioinformatics, genomics, and biological computations are gaining increased attention. Genomes of viruses can be represented by character strings based on their nucleobases. Document similarity metric...
Document image binarization is a challenging task, especially when it comes to text segmentation in degraded document images. The binarization, as a pre-processing step of Optical Character Recognition (OCR), is one of the most fundamental and common...
Document-grounded conversation (DGC) is a natural language generation task to generate fluent and informative responses by leveraging dialogue history and document(s). Recently, DGCs have focused on fine-tuning using pretrained language models. Howev...
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