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Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

Helena Gómez-Adorno, Grigori Sidorov, David Pinto, Darnes Vilariño, Alexander Gelbukh
2016 Sensors  
We apply the integrated syntactic graph feature extraction methodology to the task of automatic authorship detection.  ...  We extract textual patterns based on features obtained from shortest path walks over integrated syntactic graphs and apply them to determine the authors of documents.  ...  ISG Textual Patterns for Automatic Authorship Detection In this section, we present the application of the textual patterns extraction based on ISG for two problems associated with automatic authorship  ... 
doi:10.3390/s16091374 pmid:27589740 pmcid:PMC5038652 fatcat:ieymx7ngzzacbbodluf7bt6poe

Cognitive Network Science Reconstructs How Experts, News Outlets and Social Media Perceived the COVID-19 Pandemic

Massimo Stella
2020 Systems  
jargon rather than from science.  ...  This work uses cognitive network science to reconstruct how experts, influential news outlets and social media perceived and reported the news "COVID-19 is a pandemic".  ...  Forma Mentis Networks as Knowledge Graphs Extracted from Text This manuscript adopted the recent framework of forma mentis networks-as already introduced in previous studies-that used automatic text processing  ... 
doi:10.3390/systems8040038 fatcat:tukargwz55d7npaecwiq75q3t4

Editorial

Bing Liu, Kevin Chen-Chuan-Chang
2004 SIGKDD Explorations  
Automatic methods aim to find patterns/grammars from the Web pages and then use them to extract data.  ...  In order to make use of or to extract information from multiple sites to provide value added services, e.g., metasearch, deep Web search, etc, one needs to semantically integrate information from multiple  ... 
doi:10.1145/1046456.1046457 fatcat:zheeoyqhdrblza3jdm3qrtaavy

A Method for Thematic and Structural Visualization of Academic Content

Alexander Amigud, Joan Arnedo-Moreno, Thanasis Daradoumis, Ana-Elena Guerrero-Roldan
2017 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)  
reasonable level of academic integrity.  ...  I cried because he would never do them again, he would never carve another piece of wood or help us raise doves and pigeons in the backyard or play the violin the way he did, or tell us jokes the way he  ...  The first two types rely on human invigilators to detect misconduct, while the last is applying pattern recognition techniques to detect anomalies in an automatic fashion.  ... 
doi:10.1109/icalt.2017.24 dblp:conf/icalt/AmigudADG17 fatcat:voezr7hg6nfcxlubzzgsbnzpi4

Content-based citation analysis: The next generation of citation analysis

Ying Ding, Guo Zhang, Tamy Chambers, Min Song, Xiaolong Wang, Chengxiang Zhai
2014 Journal of the Association for Information Science and Technology  
Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge  ...  Content-based citation analysis (CCA) addresses a citation's value by interpreting each based on their contexts at both syntactic and semantic level.  ...  Their methodology involved automatic classification through supervised learning classifiers using the textual, physical, and syntactic feature sets.  ... 
doi:10.1002/asi.23256 fatcat:7gethjhuzva4nejqnd4uthpogi

Academic Plagiarism Detection

Tomáš Foltýnek, Norman Meuschke, Bela Gipp
2019 ACM Computing Surveys  
Concluding from our analysis, we see the integration of heterogeneous analysis methods for textual and non-textual content features using machine learning as the most promising area for future research  ...  These improvements mainly originate from better semantic text analysis methods, the investigation of non-textual content features, and the application of machine learning.  ...  Hamza and Salim [182] employed SRL to extract arguments from sentences, which they used to quantify and compare the syntactic and semantic similarity of the sentences. Ferreira et al.  ... 
doi:10.1145/3345317 fatcat:yk6f5xl2kvdxlhvsolem6zfdsu

Analyzing Non-Textual Content Elements to Detect Academic Plagiarism

Norman Meuschke, Bela Gipp, Harald Reiterer, Michael L. Nelson
2021 Zenodo  
To demonstrate the benefit of combining non-textual and text-based detection methods, the thesis describes the first plagiarism detection system that integrates th [...]  ...  Subsequently, the thesis summarizes work that initiated the research on analyzing non-textual content elements to detect academic plagiarism by studying citation patterns in academic documents.  ...  Because textual labels are common in academic figures, we devised and integrated two methods that use Optical Character Recognition to extract and analyze text from figures, such as graphs, plots, and  ... 
doi:10.5281/zenodo.4913344 fatcat:xmpaahvwuva53l5l5i2gaidvi4

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
Compared with the best system from CoNLL-2011, which employs a rule-based method, our system shows competitive performance.  ...  Our system gives a better performance than all the learning-based systems from the CoNLL-2011 shared task on the same dataset.  ...  In this work, we propose a discourse structure-oriented classification of the comma that can be automatically extracted from the Chinese Treebank based on syntactic patterns.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

An Approach to Document Fingerprinting [chapter]

Yunhyong Kim, Seamus Ross
2015 Lecture Notes in Computer Science  
Here we present a preliminary thought experiment for fingerprinting documents using textual documents visualised and analysed at multiple scales and dimensions to explore patterns on which we might capitalise  ...  of topics, purpose of creation, structure of presentation as well as relationships to other entities expressed by authorship, ownership, production process, and geographical and temporal markers.  ...  We benefited from insightful observations by anonymous ICADL2015 reviewers.  ... 
doi:10.1007/978-3-319-27974-9_11 fatcat:sn5pk3wt6jftjmg4ajzg4xicom

A framework for authorship identification of online messages: Writing-style features and classification techniques

Rong Zheng, Jiexun Li, Hsinchun Chen, Zan Huang
2006 Journal of the American Society for Information Science and Technology  
In this framework, four types of writing-style features (lexical, syntactic, structural, and content-specific features) are extracted and inductive learning algorithms are used to build feature-based classification  ...  models to identify authorship of online messages.  ...  We also thank Detective Tim Petersen, Sergeant Jennifer Schroeder, and Daniel Casey from the Tucson Police Department for their assistance on the project.  ... 
doi:10.1002/asi.20316 fatcat:pa46dhk77jaqfdxgoao4dg54ui

Visual Analytics: Combining Automated Discovery with Interactive Visualizations [chapter]

Daniel A. Keim, Florian Mansmann, Daniela Oelke, Hartmut Ziegler
2008 Lecture Notes in Computer Science  
To further explain the Visual Analytics process, we provide examples from the area of document analysis.  ...  Visual analysis techniques extend the perceptual and cognitive abilities of humans with automatic data analysis techniques, and help to gain insights for optimizing and steering complicated processes.  ...  The visual analysis enables the analyst to detect problems with the low-level feature used and adapt the similarity measures to make the authorship attribution more effective.  ... 
doi:10.1007/978-3-540-88411-8_2 fatcat:ss2jdbz2wrdwzjmitjlumf76x4

Visual Analytics: Combining Automated Discovery with Interactive Visualizations [chapter]

Daniel A. Keim, Florian Mansmann, Daniela Oelke, Hartmut Ziegler
2008 Lecture Notes in Computer Science  
To further explain the Visual Analytics process, we provide examples from the area of document analysis.  ...  Visual analysis techniques extend the perceptual and cognitive abilities of humans with automatic data analysis techniques, and help to gain insights for optimizing and steering complicated processes.  ...  The visual analysis enables the analyst to detect problems with the low-level feature used and adapt the similarity measures to make the authorship attribution more effective.  ... 
doi:10.1007/978-3-540-87987-9_2 fatcat:zqp36pslpbg3bfn3aznvpkc4fy

The Ancient Greek and Latin Dependency Treebanks [chapter]

David Bamman, Gregory Crane
2011 Language Technology for Cultural Heritage  
This paper describes the development, composition, and several uses of the Ancient Greek and Latin Dependency Treebanks, large collections of Classical texts in which the syntactic, morphological and lexical  ...  behavior of lexemes and automatically identifying similar passages between texts.  ...  This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No.  ... 
doi:10.1007/978-3-642-20227-8_5 dblp:series/tanlp/BammanC11 fatcat:vz7fvoizmjee5bjiupzhsd6gxu

Machine Learning-based Analysis of Program Binaries: A Comprehensive Study

Hongfa Xue, Shaowen Sun, Guru Venkataramani, Tian Lan
2019 IEEE Access  
Binary code analysis is crucial in various software engineering tasks, such as malware detection, code refactoring, and plagiarism detection.  ...  To meet these challenges, machine learning-based binary code analysis frameworks attract substantial attention due to their automated feature extraction and drastically reduced efforts needed on large-scale  ...  In general, the goal of feature extraction is to automatically link binary code patterns mined at the lexical level with patterns mined at the syntactic level. A.  ... 
doi:10.1109/access.2019.2917668 fatcat:fwjpykkdpjev7pzkhaoily4zci

Perspectives of the performance metrics in lexicon and hybrid based approaches: a review

Meesala Shobha Rani, Sumathy S
2017 International Journal of Engineering & Technology  
Semantic detection is the sub-class in the sentiment analysis which is used for measuring the sentiment orientation in any text. Opinionated text is used for analyzing and making the decision simple.  ...  This interdisciplinary field draws various techniques from data mining, machine learning, natural language processing, lexicon based and hybrid based approaches.  ...  A methodology termed temporal semantic relations, which integrate the connection entity, lexical syntactic patterns, context sentences, context graph and context communities achieving highest precision  ... 
doi:10.14419/ijet.v6i4.8295 fatcat:uyrcl7z2o5fzrkfngxt76rt7we
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