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Hierarchical Graph Convolutional Networks for Structured Long document Classification

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第10期34卷 8071-8085页

作者： Liu, Tengfei Hu, Yongli Wang, Boyue Sun, Yanfeng Gao, Junbin Yin, Baocai Beijing Univ Technol Fac Informat Technol Beijing Inst Artificial Intelligence Beijing Key Lab Multimedia & Intelligent Software Beijing 100124 Peoples R China Univ Sydney Business Sch Discipline Business Analyt Camperdown NSW 2006 Australia

Long document classification (LDC) has been a focused interest in natural language processing (NLP) recently with the exponential increase of publications. Based on the pretrained language models, many LDC methods have been proposed and achieved considerable progression. However, most of the existing methods model long documents as sequences of text while omitting the document structure, thus limiting the capability of effectively representing long texts carrying structure information. To mitigate such limitation, we propose a novel hierarchical graph convolutional network (HGCN) for structured LDC in this article, in which a section graph network is proposed to model the macrostructure of a document and a word graph network with a decoupled graph convolutional block is designed to extract the fine-grained features of a document. In addition, an interaction strategy is proposed to integrate these two networks as a whole by propagating features between them. To verify the effectiveness of the proposed model, four structured long document datasets are constructed, and the extensive experiments conducted on these datasets and another unstructured dataset show that the proposed method outperforms the state-of-the-art related classification methods.

关键词： Transformers Context modeling Computational modeling Complexity theory Task analysis Analytical models Feature extraction Decoupled graph convolution document and text processing graph pooling hierarchical graph convolutional networks (HGCNs) long document classification (LDC)

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Visual Readability Analysis: How to Make Your Writings Easier to Read

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2012年第5期18卷 662-674页

作者： Oelke, Daniela Spretke, David Stoffel, Andreas Keim, Daniel A. Univ Konstanz Dept Comp & Informat Sci D-78457 Constance Germany

We present a tool that is specifically designed to support a writer in revising a draft version of a document. In addition to showing which paragraphs and sentences are difficult to read and understand, we assist the reader in understanding why this is the case. This requires features that are expressive predictors of readability, and are also semantically understandable. In the first part of the paper, we, therefore, discuss a semiautomatic feature selection approach that is used to choose appropriate measures from a collection of 141 candidate readability features. In the second part, we present the visual analysis tool VisRA, which allows the user to analyze the feature values across the text and within single sentences. Users can choose between different visual representations accounting for differences in the size of the documents and the availability of information about the physical and logical layout of the documents. We put special emphasis on providing as much transparency as possible to ensure that the user can purposefully improve the readability of a sentence. Several case studies are presented that show the wide range of applicability of our tool. Furthermore, an in-depth evaluation assesses the quality of the measure and investigates how well users do in revising a text with the help of the tool.

关键词： document and text processing feature evaluation and selection

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A scale space approach for automatically segmenting words from historical handwritten documents

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2005年第8期27卷 1212-1225页

作者： Manmatha, R Rothfeder, JL Univ Massachusetts Ctr Intelligent Informat Retrieval Dept Comp Sci Amherst MA 01003 USA

Many libraries, museums, and other organizations contain large collections of handwritten historical documents, for example, the papers of early presidents like George Washington at the Library of Congress. The first step in providing recognition/retrieval tools is to automatically segment handwritten pages into words. State of the art segmentation techniques like the gap metrics algorithm have been mostly developed and tested on highly constrained documents like bank checks and postal addresses. There has been little work on full handwritten pages and this work has usually involved testing on clean artificial documents created for the purpose of research. Historical manuscript images, on the other hand, contain a great deal of noise and are much more challenging. Here, a novel scale space algorithm for automatically segmenting handwritten ( historical) documents into words is described. First, the page is cleaned to remove margins. This is followed by a gray-level projection profile algorithm for finding lines in images. Each line image is then filtered with an anisotropic Laplacian at several scales. This procedure produces blobs which correspond to portions of characters at small scales and to words at larger scales. Crucial to the algorithm is scale selection, that is, finding the optimum scale at which blobs correspond to words. This is done by finding the maximum over scale of the extent or area of the blobs. This scale maximum is estimated using three different approaches. The blobs recovered at the optimum scale are then bounded with a rectangular box to recover the words. A postprocessing filtering step is performed to eliminate boxes of unusual size which are unlikely to correspond to words. The approach is tested on a number of different data sets and it is shown that, on 100 sampled documents from the George Washington corpus of handwritten document images, a total error rate of 17 percent is observed. The technique outperforms a state-of-the-art gap met

关键词： segmentation document and text processing document analysis handwriting analysis document indexing smoothing optical character recognition

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document IMAGE BINARISATION USING A SUPERVISED NEURAL NETWORK

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INTERNATIONAL JOURNAL OF NEURAL SYSTEMS 2008年第5期18卷 405-418页

作者： Khashman, Adnan Sekeroglu, Boran Near East Univ Dept Elect & Elect Engn TR-10 Lefkosa Mersin Turkey Near East Univ Dept Comp Engn TR-10 Lefkosa Mersin Turkey

Advances in digital technologies have allowed us to generate more images than ever. Images of scanned documents are examples of these images that form a vital part in digital libraries and archives. Scanned degraded documents contain background noise and varying contrast and illumination, therefore, document image binarisation must be performed in order to separate foreground from background layers. Image binarisation is performed using either local adaptive thresholding or global thresholding;with local thresholding being generally considered as more successful. This paper presents a novel method to global thresholding, where a neural network is trained using local threshold values of an image in order to determine an optimum global threshold value which is used to binarise the whole image. The proposed method is compared with five local thresholding methods, and the experimental results indicate that our method is computationally cost-effective and capable of binarising scanned degraded documents with superior results.

关键词： Image enhancement binarisation thresholding neural network document and text processing

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Verification of dynamic curves extracted from static handwritten scripts

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PATTERN RECOGNITION 2008年第12期41卷 3773-3785页

作者： Nel, Emli-Mari du Preez, J. A. Herbst, B. M. Univ Stellenbosch Dept Appl Math ZA-7602 Matieland South Africa Univ Stellenbosch Dept Elect & Elect Engn ZA-7602 Matieland South Africa

Static handwritten scripts originate as images on documents and do not, by definition, contain any dynamic information. To improve the accuracy of static handwriting recognition systems, many techniques aim to estimate dynamic information from the static scripts. Mostly, the pen trajectories of the scripts are estimated. However, the efficacy of the resulting pen trajectories are rarely evaluated quantitatively. This paper proposes a protocol for the objective evaluation of automatically determined pen trajectories. A hidden Markov model is derived from a ground-truth trajectory. An estimated trajectory is then matched to the derived model. Statistics describing substitution, insertion and deletion errors are then computed from this match. The proposed algorithm is especially useful for performance comparisons between different pen trajectory estimation algorithms. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： pattern recognition document and text processing document analysis handwriting analysis estimating pen trajectories of static scripts automatic assessment stroke recovery

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Event Detection in Twitter Microblogging

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IEEE TRANSACTIONS ON CYBERNETICS 2016年第12期46卷 2810-2824页

作者： Doulamis, Nikolaos D. Doulamis, Anastasios D. Kokkinos, Panagiotis Varvarigos, Emmanouel (Manos) Natl Tech Univ Athens GR-15773 Athens Greece Univ Patras Comp Engn & Informat Dept Patras 26504 Greece

The millions of tweets submitted daily overwhelm users who find it difficult to identify content of interest revealing the need for event detection algorithms in Twitter. Such algorithms are proposed in this paper covering both short (identifying what is currently happening) and long term periods (reviewing the most salient recently submitted events). For both scenarios, we propose fuzzy represented and timely evolved tweet-based theoretic information metrics to model Twitter dynamics. The Riemannian distance is also exploited with respect to words' signatures to minimize temporal effects due to submission delays. Events are detected through a multiassignment graph partitioning algorithm that: 1) optimally retains maximum coherence within a cluster and 2) while allowing a word to belong to several clusters (events). Experimental results on real-life data demonstrate that our approach outperforms other methods.

关键词： Clustering document and text processing fuzzy representation pattern analysis tweet characterization

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A Semantic-Based Solution for UBL Schema Interoperability

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IEEE INTERNET COMPUTING 2009年第3期13卷 64-71页

作者： Yarimagan, Yalin Dogac, Asuman Middle E Tech Univ Dept Comp Engn Ankara Turkey

The Universal Business Language (UBL) is an initiative to develop common business document schemas for interoperability. However, businesses operate in different industry, geopolitical, and regulatory contexts and have different rules and requirements for the information they exchange. So, several trading communities are tailoring UBL schemas to their needs, requiring that these schemas translate to each other. In this article, the authors describe how to enhance UBL with semantics-based translation mechanisms to maintain interoperability between documents conforming to different schema versions.

关键词： Data Mapping Interoperability Software Engineering Standards document Preparation document and text processing Computing Methodologies Electronic Commerce

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Reconstructing the frontal geometry of drawings of arbitrary surfaces

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COMPUTERS & GRAPHICS-UK 2007年第4期31卷 568-579页

作者： Kaplan, Matthew Cohen, Elaine Univ Utah Salt Lake City UT 84112 USA

We present a method for creating 2 1/2D models from line drawings of opaque solid objects. As input, we use a single drawing composed of strokes indicative of surface geometry, but not of texture, color or shading. We attempt to allow the artist to draw naturally, differing from many previous approaches. Our system allows both perspective and orthographic projection to be used and we make no a priori assumptions about the type of model to be produced (i.e. planar, curved, normalon). The frontal geometry of the input drawing is reconstructed by placing constraints at the contours and solving a 2D variational system for the smoothest piecewise smooth surface. An analysis of line labelling allows us to determine what constraints are possible and/or required for each input line. However, because line labelling produces a combinatorial explosion of valid output geometries, we allow the user to guide the constraint selection and optimization with a simple user interface that abstracts the technical details away from the user. The system produces candidate reconstructions using different constraint values, from which the user selects the one that most closely approximates the model represented by the drawing. These choices allow the system to determine the constraints and reconstruct the model. The system runs at interactive speeds. (c) 2007 Published by Elsevier Ltd.

关键词： artificial intelligence perceptual reasoning computer graphics computational geometry and object modelling document and text processing graphics recognition and interpretation

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Estimating the pen trajectories of static signatures using hidden Markov models

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2005年第11期27卷 1733-1746页

作者： Nel, EM du Preez, JA Herbst, BM Univ Stellenbosch Dept Elect & Elect Engn ZA-7602 Matieland South Africa Univ Stellenbosch Dept Appl Math ZA-7602 Matieland South Africa

Static signatures originate as handwritten images on documents and by definition do not contain any dynamic information. This lack of information makes static signature verification systems significantly less reliable than their dynamic counterparts. This study involves extracting dynamic information from static images, specifically the pen trajectory while the signature was created. We assume that a dynamic version of the static image is available (typically obtained during an earlier registration process). We then derive a hidden Markov model from the static image and match it to the dynamic version of the image. This match results in the estimated pen trajectory of the static image.

关键词： pattern recognition document and text processing document analysis handwriting analysis

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A pseudo-skeletonization algorithm for static handwritten scripts

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INTERNATIONAL JOURNAL ON document ANALYSIS AND RECOGNITION 2009年第1期12卷 47-62页

作者： Nel, Emli-Mari du Preez, J. A. Herbst, B. M. Oxford Metr Grp Oxford OX2 0JB England Univ Stellenbosch Dept Elect & Elect Engn ZA-7602 Matieland South Africa Univ Stellenbosch Dept Appl Math ZA-7602 Matieland South Africa

This paper describes a skeletonization approach that has desirable characteristics for the analysis of static handwritten scripts. We concentrate on the situation where one is interested in recovering the parametric curve that produces the script. Using Delaunay tessellation techniques where static images are partitioned into sub-shapes, typical skeletonization artifacts are removed, and regions with a high density of line intersections are identified. An evaluation protocol, measuring the efficacy of our approach is described. Although this approach is particularly useful as a pre-processing step for algorithms that estimate the pen trajectories of static signatures, it can also be applied to other static handwriting recognition techniques.

关键词： Skeletonization Thinning Pseudo skeleton document and text processing document analysis

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