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Extraction and analysis of text patterns from NSFW adult content in Reddit

DATA & KNOWLEDGE ENGINEERING 2022年 138卷 101979-101979页

作者： Cauteruccio, Francesco Corradini, Enrico Terracina, Giorgio Ursino, Domenico Virgili, Luca Univ Calabria DEMACS Calabria Italy Polytech Univ Marche DII Ancona Italy

Reddit is one of the few social networks that handles Not Safe For Work (NSFW) content in an explicit and well-structured way. Despite this, in the past literature on Reddit, there are very few researches concerning this topic. In particular, a study on the text of NSFW comments and posts published in this social medium is missing. In this paper, we aim at contributing to fill this gap by proposing an approach for extracting and analyzing text patterns from NSFW adult content in Reddit. Some peculiarities of our approach are the following: (i) text patterns are extracted based not only on frequency but also, and mostly, on several utility measures;(ii) extracted patterns contribute to the definition of social networks whose analysis allows us to extract several useful information about the users publishing and/or accessing NSFW content and the language adopted by them;(iii) our approach is not only descriptive but also predictive, because, in addition to identifying already existing user communities, it is able to propose new ones;these are made up of users who do not yet know each other but share the same interests and the same language.

关键词： Reddit NSFW posts and comments text patterns Pattern utility measures Social Network Analysis Triads and cliques

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Exploring the Traits of Manual E-Mail Categorization text patterns

Exploring the Traits of Manual E-Mail Categorization Text Pa...

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9th International Conference on Natural Language Processing (NLP)

作者： Sneiders, Eriks Eriksson, Gunnar Alfalahi, Alyaa Stockholm Univ Dept Comp & Syst Sci SE-16440 Kista Sweden

ISBN: (纸本)9783319108889;9783319108872

Automated e-mail answering with a standard answer is a text categorization task. text categorization by matching manual text patterns to messages yields good performance if the text categories are specific. Given that manual text patterns embody informal human perception of important wording in a written inquiry, it is interesting to investigate more formal traits of this important wording, such as the amount of matching text, distance between matching words, n-grams, part-of-speech patterns, and vocabulary in the matching words. Understanding these features may help us better design text-pattern extraction algorithms.

关键词： text patterns part-of-speech patterns POS patterns

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An investigation on not safe for work adult content in Reddit 29

An investigation on not safe for work adult content in Reddi...

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29th Italian Symposium on Advanced Database Systems, SEBD 2021

作者： Cauteruccio, Francesco Corradini, Enrico Terracina, Giorgio Ursino, Domenico Virgili, Luca DEMACS University of Calabria Italy DII Polytechnic University of Marche Italy

Reddit is one of the few social platforms that handles NSFW (Not Safe For Work) content in an explicit and well-structured way. Despite this fact, such an issue has been very neglected in the past by researchers who have studied this social network. In this paper, we aim at providing a contribution in this setting by proposing an approach to extract and analyze text patterns from NSFW content in Reddit. An important peculiarity of our approach is that patterns are extracted not only based on their frequency (as it generally happens in the past literature), but also, and especially, on one or more utility measures. © 2021 Copyright for this paper by its authors.

关键词： NSFW posts and comments Pattern utility measures Reddit Social network analysis text patterns

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FLAG-PDFe: Features Oriented Metadata Extraction Framework for Scientific Publications

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IEEE ACCESS 2020年 8卷 99458-99469页

作者： Ahmed, Muhammad Waqas Afzal, Muhammad Tanvir Capital Univ Sci & Technol Dept Comp Sci Islamabad 44000 Pakistan

The unprecedented growth of the research publications in diversified domains has overwhelmed the research community. It requires a cumbersome process to extract this enormous information by manually analyzing these research documents. To automatically extract content of a document in a structured way, metadata and content must be annotated. Scientific community has been focusing on automatic extraction of content by forming different heuristics and applying different machine learning techniques. One of the renowned conference organizers, ESWC organizes state-of-the-art challenge to extract metadata like authors, affiliations, countries in affiliations, supplementary material, sections, table, figures, funding agencies, and EU funded projects from PDF files of research articles. We have proposed a feature centric technique that can be used to extract logical layout structure of articles from publishers with diversified composition styles. To extract unique metadata from a research article placed in logical layout structure, we have developed a four-staged novel approach "FLAG-PDFe". The approach is built upon distinct and generic features based on the textual and the geometric information from the raw content of research documents. At the first stage, the distinct features are used to identify different physical layout components of an individual article. Since research journals follow their unique publishing styles and layout formats, therefore, we develop generic features to handle these diversified publishing patterns. We employ support vector classification (SVC) in the third stage to extract the logical layout structure (LLS)/ sections of an article, after performing comprehensive evaluation of generic features and machine learning models. Finally, we further apply heuristics on LLS to extract the desired metadata of an article. The outcomes of the study are obtained using the gold standard data set. The results yields 0.877 recall, precision 0.928 and 0.897 F-m

关键词： Feature extraction Metadata Layout Portable document format Data mining Machine learning Support vector machines Machine learning research article metadata extraction text patterns document structure analysis

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Improved Learning of Academic Writing Reducing Complexity by Modeling Academic texts 10

Improved Learning of Academic Writing Reducing Complexity by...

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10th International Conference on Computer Supported Education (CSEDU)

作者： Faustmann, Gert Berlin Sch Econ & Law Dept Cooperat Studies Alt Friedrichsfelde 60 D-10315 Berlin Germany

ISBN: (纸本)9789897582912

A graphical modeling language for scientific texts is presented, which particularly supports the learning process of academic writing. The supervision process for textual work in higher education is often characterized by misunderstandings, since the agreements are based on the abstract level of the document outline. The written text then often misses an inner structure and suitable representations and thus has little coherence. Since an academic text is a complex combination of text segments, linguistic functions, content, and means of presentation, a notation is proposed that includes these different perspectives. Based on the UML for software modeling, extracts of a text as well as different levels of abstraction can so be part of the learning process. Finally, a software tool is sketched, which can support the construction of document frameworks as well as the creation of the actual text.

关键词： text Coherence Writing Process Argument Representation text Perspectives text patterns

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Automated email answering by text-pattern matching: Performance and error analysis

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EXPERT SYSTEMS 2018年第1期35卷 1-1页

作者： Sneiders, Eriks Sjoebergh, Jonas Alfalahi, Alyaa Stockholm Univ Stockholm Sweden Hokkaido Univ Sapporo Hokkaido Japan

Automated answering of frequent email inquiries can be implemented as a text categorization task with narrow text categories, where all messages in 1 text category have the same answer. Such email categorization should be optimized for high precision and at least acceptable recall. One such high-precision email categorization method is matching of surface text patterns to incoming email messages. In order to assess the upper performance limits of text-pattern matching, we conducted extensive tests with almost 10,000 messages. Our results show that automated email answering with precision around 90% and recall 50-75% is feasible. In order to achieve this, however, the system must work with multiword expressions rather than stand-alone words. Furthermore, we argue that the system has to distinguish the context of an email inquiry from the actual need that created the inquirya question, request, or complaint. We have discovered and analysed 12 reasons why text-pattern matching may fail.

关键词： automated email answering email categorization question answering text patterns

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Increasing Comprehension of Expository Science text for Students With Autism Spectrum Disorder

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FOCUS ON AUTISM AND OTHER DEVELOPMENTAL DISABILITIES 2016年第3期31卷 208-220页

作者： Carnahan, Christina R. Williamson, Pamela Birri, Nicole Swoboda, Christopher Snyder, Kate K. Univ Cincinnati Cincinnati OH 45221 USA Univ N Carolina Greensboro NC USA Warren Cty Educ Serv Ctr Lebanon OH USA Springfield Coll Springfield MA USA

Using a multiple baseline single-subject design, this study evaluated the effects of a text structure intervention package on the ability of students with autism to comprehend traditional science texts. Three high school students with high-functioning autism and their teacher participated in this study. The intervention package included instruction in types of text structures using a text structure organization sheet before reading, and completing an analysis and summary sheet during and after reading. Results indicated that the instruction was highly effective during intervention and maintenance phase for all three participants. The first-year special education teacher was able to implement the intervention with fidelity. All participants agreed that the intervention was helpful for reading science texts. Future research and implications for classroom intervention is discussed.

关键词： autism spectrum disorder reading text patterns

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Performance Evaluation of Nature - Inspired Optimization Techniques in Disentangling text Pattern Overlaps

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JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING 2014年第5-6期23卷 503-527页

作者： Rajaraman, Sivaramakrishnan Vaidyanathan, Ganesh Chokkalingam, Arun SSN Coll Engn Dept Biomed Engn Kalavakkam 603110 Tamil Nadu India Sri Venkateswara Coll Engn Dept Elect & Commun Engn Sriperumbudur 602117 Tamil Nadu India RMK Coll Engn & Technol Dept Elect & Commun Engn Kavarapettai 601206 Tamil Nadu India

This paper evaluates the performance of nature-inspired, optimization techniques including Firefly Algorithm (FA), Simulated Annealing (SA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in resolving occlusions in text patterns. These Optimization techniques work individually on a randomly extracted population, from the occluded text strings. FA performs at its best by resolving occlusions even when 80% of a text string is hidden under the other. The brightness of the fireflies is associated with the objective function to be optimized and the algorithm assumes idealized rules for attractiveness and brightness and updates the position of the fireflies to reach a global optimum value. The text patterns are resolved and individually identified after a certain number of iterations. The selection of FA as the best in disentangling text strings is validated with the one-way Analysis of Variance (ANOVA) statistical tool, followed by Tukey's post-hoc test.

关键词： Nature-inspired optimization occlusion text patterns disentangle objective function firefly algorithm (FA) simulated annealing (SA) genetic algorithm (GA) particle swarm optimization (PSO) analysis of variance (ANOVA) Tukey's post-hoc test

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Automated Email Answering by text Pattern Matching

Automated Email Answering by Text Pattern Matching

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7th International Conference on Natural Language Processing

作者： Sneiders, Eriks Stockholm Univ Dept Comp & Syst Sci SE-16440 Kista Sweden

ISBN: (纸本)9783642147692

Answering email by standard answers is a common practice at contact centers. Our research assists this process by creating reply messages that contain one or several standard answers. Our standard answers are linked to representative text patterns that match incoming messages. The system works in three languages. The performance was evaluated on two email sets;the main advantage of our email answering technique is good correctness of the delivered replies.

关键词： Automated email answering automatic email response text message answering question answering text patterns

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A graphical, self-organizing approach to classifying electronic meeting output

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JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE 1997年第2期48卷 157-170页

作者： Orwig, RE Chen, HC Nunamaker, JF UNIV ARIZONA COLL BUSINESS & PUBL ADMMIS DEPTTUCSONAZ 85721

This article describes research in the application of a Kohonen Self-Organizing Map (SOM) to the problem of classification of electronic brainstorming output and an evaluation of the results. Electronic brainstorming is one of the most productive tools in the Electronic Meeting System called GroupSystems. A major step in group problem solving involves the classification of electronic brainstorming output into a manageable list of concepts, topics, or issues that can be further evaluated by the group. This step is problematic due to information overload and the cognitive demand of processing a large quantity of textual data. This research builds upon previous work in automating the meeting classification process using a Hopfield neural network. Evaluation of the Kohonen output comparing it with Hopfield and human expert output using the same set of data found that the Kohonen SOM performed as well as a human expert in representing term association in the meeting output and outperformed the Hopfield neural network algorithm. In addition, recall of consensus meeting concepts and topics using the Kohonen algorithm was equivalent to that of the human expert. However, precision of the Kohonen results was poor, The graphical representation of textual data produced by the Kohonen SOM suggests many opportunities for improving information organization of textual information. Increasing uses of electronic mail, computer-based bulletin board systems, and world-wide web services present unique challenges and opportunities for a system-aided classification approach. This research has shown that the Kohonen SOM may be used to automatically create ''a picture that can represent a thousand (or more) words.''

关键词： Algorithms Artificial Intelligence Brainstorming Classification Computer Mediated Communication Computer Oriented Programs Computer System Design Group Discussion MapsSelf Organizing Maps textual Analysis text patterns Kohonen (Teuvo)

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