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A Modular Metadata Extraction System for Born-Digital Articles
2012
2012 10th IAPR International Workshop on Document Analysis Systems
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We present a comprehensive system for extracting metadata from scholarly articles. ...
The evaluation tests we have performed showed good results of the individual implementations and the entire metadata extraction process. ABSTRACT 163 3 21 AFFILIATION ...
We would also like to thank the anonymous reviewers for their insightful comments. ...
doi:10.1109/das.2012.4
dblp:conf/das/TkaczykBCR12
fatcat:fly4braehnafhjk6xz6z5ulffy
Multimodal Approach for Metadata Extraction from German Scientific Publications
[article]
2021
arXiv
pre-print
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Our model for this approach was trained on a dataset consisting of around 8800 documents and is able to obtain an overall F1-score of 0.923. ...
This model aims to increase the overall accuracy of metadata extraction compared to other state-of-the-art approaches. ...
[17] , numerous previous old studies on metadata extraction relied on text and layout rules, addressing the issue using context-based classifiers such as Hidden Markov Models (HMMs) and similar approaches ...
arXiv:2111.05736v1
fatcat:rz5xwg5nkrhz7hwn54by2eqcpa
KEYRY: A Keyword-Based Search Engine over Relational Databases Based on a Hidden Markov Model
[chapter]
2011
Lecture Notes in Computer Science
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In KEYRY the search process is modeled as a Hidden Markov Model and the List Viterbi algorithm is applied to computing the top-k queries that better represent the intended meaning of a user keyword query ...
This work was partially supported by project "Searching for a needle in mountains of data" ...
The tool we demonstrate here is instead based on a Hidden Markov Model. A detailed description of the methodology can be found on our respective research paper [2] . ...
doi:10.1007/978-3-642-24574-9_42
fatcat:fa7npu7g5vhhtibfp6xoe5mk34
Sequence Labeling using Conditional Random Fields
2017
International Journal of u- and e- Service, Science and Technology
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Conditional random fields (CRFs), is a scheme for building probabilistic models to divide and tag sequence data. ...
With a given a labeled set of data, baseline set of features will be created and the accuracy of the CRF suite model created using those features will be measured. ...
It represents the large literature body and it also studies the particular class of Hidden Markov Model It is an undirected graphical model which is conditionally trained, repeated over sequence. ...
doi:10.14257/ijunesst.2017.10.9.10
fatcat:pofo2sdqazgfjgt3bvnsn5ibmi
Detection of Mobile Phone Fraud Using Possibilistic Fuzzy C-Means Clustering and Hidden Markov Model
2016
International Journal of Synthetic Emotions
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This paper presents a novel approach for fraud detection in mobile phone networks by using a combination of Possibilistic Fuzzy C-Means clustering and Hidden Markov Model (HMM). ...
The trained HMM model is then applied for detecting fraudulent activities on incoming call sequences. ...
Markov Model (HMM). ...
doi:10.4018/ijse.2016070102
fatcat:xjjuucmiz5dynnc4tlwyjnbd5u
A Rule-Based Information Extraction Approach for Extracting Metadata from PDF Books
2021
Innovative Computing Information and Control Express Letters, Part B: Applications
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In this work, an intelligent rule-based approach is proposed for extracting the logical metadata from PDF books accurately. ...
The experimental results indicate that the proposed approach is capable of extracting the metadata from PDF books successfully with an overall accuracy of 94.62% and 90.27% for both training and testing ...
Finally, the Hidden Markov Model (HMM) is applied for extracting the authors and the titles. ...
doi:10.24507/icicelb.12.02.121
fatcat:4kjs4omuxvhrnhujft5ad7maca
Analyzing the Dynamics of Research by Extracting Key Aspects of Scientific Papers
2011
International Joint Conference on Natural Language Processing
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We extract these characteristics by matching semantic extraction patterns, learned using bootstrapping, to the dependency trees of sentences in an article's abstract. ...
For instance, we show that part-of-speech tagging and parsing have increasingly been adopted as tools for solving problems in other domains. ...
papers mainly due to techniques like expectation maximization and hidden Markov models. ...
dblp:conf/ijcnlp/GuptaM11
fatcat:d56yguykize7jdxmndcs6b6n3y
Research on the Application of User Behavior Auditing Based on Hidden Markov Model in Cloud Environment
2017
DEStech Transactions on Materials Science and Engineering
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A user behavior modeling method based on Hidden Markov model is proposed in this paper, the user behavior model is used to identify the validity of the user's operation, and to ensure the security of the ...
In the process of audit data analysis and processing, a feature vector method is proposed to extract valuable information from audit data. ...
Hidden Markov model is actually a classification method in data mining, using the hidden Markov model to model the normal behavior of cloud users. ...
doi:10.12783/dtmse/icmsme2016/7516
fatcat:voumabvizfhhpkwsgwahklfrea
Prediction is very hard, especially about conversion. Predicting user purchases from clickstream data in fashion e-commerce
[article]
2019
arXiv
pre-print
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from the literature; finally, we propose a new discriminative neural model that outperforms neural architectures recently proposed at Rakuten labs. ...
Knowing if a user is a buyer vs window shopper solely based on clickstream data is of crucial importance for ecommerce platforms seeking to implement real-time accurate NBA (next best action) policies. ...
The authors also wish to thank Tooso Inc. for providing the computational infrastructure and funding for the project. ...
arXiv:1907.00400v1
fatcat:qjs2gqh6fff73pme2bqdlty7ty
Unsupervised Metadata Extraction in Scientific Digital Libraries Using A-Priori Domain-Specific Knowledge
2006
Semantic Web Applications and Perspectives
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More specifically, we focus on quality improvements of metadata extraction from scientific papers (mainly in computer science domain) collected from various sources over the Internet. ...
We propose and present a novel approach focusing on the improvement in the metadata extraction quality without involving external information sources (oracles, manually prepared databases, etc), but relying ...
Application of statistical models like Hidden Markov Model (HMM) [13] and Dual and Variable-length output Hidden Markov Model (DVHMM) [14] are reported to have nearly 90% accuracy however, the training ...
dblp:conf/swap/IvanyukovichM06
fatcat:h7ktkv3cyjdbfm24jjywlt7vki
Text Mining to Facilitate Domain Knowledge Discovery
[chapter]
2019
Text Mining - Analysis, Programming and Application [Working Title]
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The research includes three major parts: (1) structuralization of geological literature, (2) information extraction and visualization for geological literature, and (3) geological text mining to assist ...
For these data, traditional research methods have limited functions for integrating and mining them to make knowledge discovery. ...
The statistically based methods include machine learning and deep learning methods, such as hidden Markov model (HMM), maximum entropy Markov model (MEMM), conditional random fields (CRF), and long short-term ...
doi:10.5772/intechopen.85362
fatcat:opipq2cyhrfmjdnw2rewku7spy
Turning hamburgers into a cow - An introductory comparison of PDF metadata extraction using two reference management systems
2016
Figshare
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The sections of this paper examine the literature related to attempts to extract PDF metadata using automated harvesting technologies and the role of reference management systems in PDF organization for ...
., (2011) notes that even though PDF is the format of choice for an overwhelming majority of downloaded scholarly content, attempts to extract meaning from PDFs as they are currently used is similar to ...
Markov models; CRF -conditional random fields). ...
doi:10.6084/m9.figshare.3807183
fatcat:hromvcfbkbfydao3wlurmhcwoi
Challenging Aspects for Facial Feature Extraction and Age Estimation
2016
Indian Journal of Science and Technology
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The face identification, tools for extraction, feature normalization, features to be extracted is all explained. ...
In this paper we have discussed the steps for facial age estimation and a comparative study of various methodologies in each step has been briefed. ...
DCT coefficients of image block are used as observation vectors of an embedded HMM(Hidden Markov Model). ...
doi:10.17485/ijst/2016/v9i4/72315
fatcat:7p4wv4lhhzdkdhfc2gye7d5cnu
MexPub: Deep Transfer Learning for Metadata Extraction from German Publications
[article]
2021
arXiv
pre-print
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In this paper, we present a method that extracts metadata from PDF documents with different layouts and styles by viewing the document as an image. ...
Our method achieved an average accuracy of around 90% which validates its capability to accurately extract metadata from a variety of PDF documents with challenging templates. ...
Therefore, most of the earlier works addressed the problem of classifying segment strings in scientific documents using context-based classifiers such as Hidden Markov Models (HMMs) [26] and Conditional ...
arXiv:2106.07359v1
fatcat:k5446qbqvzhonj32urjqvaagpq
Reference metadata extraction using a hierarchical knowledge representation framework
2007
Decision Support Systems
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Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. ...
In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. ...
Acknowledgements We would like to thank the anonymous reviewers for their valuable comments, which have greatly improved the presentation of this paper. ...
doi:10.1016/j.dss.2006.08.006
fatcat:6fumdfsmdnaxjnqcyxayeqfpma
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