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

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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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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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Disciplinary variation in automatic sublanguage term identification

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JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE 1997年第1期48卷 67-79页

作者： Haas, SW UNIV N CAROLINA SCH LIB & INFORMAT SCI CB 3360 100 MANNING HALL CHAPEL HILL NC 27599 USA

The research presented here describes a method for automatically identifying sublanguage (SL) domain terms and revealing the patterns in which they occur in text, By applying this method to abstracts from a variety of disciplines, differences in how SL domain terminology occurs can be discerned, Results of this research have both practical and theoretical implications, These include 1) the identification of patterns of domain term occurrence, 2) a step toward the identification of families of SLs that share term occurrence patterns, 3) a domain term extraction procedure that can exploit the term occurrence patterns, and 4) evidence to support the intuitive notion of a continuum of ''technicality'' of disciplines and their SLs, The investigation revealed relatively consistent differences between the hard sciences, such as physics or biology, and the social sciences and humanities, such as history or sociology. The hard sciences tended to have more domain terms, and more of these terms occurred in sequences than in the social sciences and humanities. The seed terms used in this research occurred adjacent to domain terms more often in the hard sciences than in the social sciences, The extraction process was more successful in the hard science disciplines than in the social sciences, identifying more of the domain terms while extracting fewer general terms.

关键词： Abstracts Automation Classification Comparative Analysis Intellectual Disciplines Natural Sciences Social Sciences Subject Index Terms Tables (Data) VocabularySublanguage Grammars textual Analysis text patterns

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N-GRAMS AND THEIR IMPLICATION TO NATURAL-LANGUAGE UNDERSTANDING

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PATTERN RECOGNITION 1990年第5期23卷 509-528页

作者： YANNAKOUDAKIS, EJ TSOMOKOS, I HUTTON, PJ Postgraduate School of Computer Science University of Bradford Bradford West Yorkshire BD 1DP U.K

This paper presents the results of a comparative information-theoretic study that was carried out between Greek and English texts. The rank frequency correlation (p) between the two appears to be very high; the correlation is between 0.915 and 0.989. The results also include positional letter analyses, n-gram analyses, word analyses, empirical semantic correlations between the Greek and English n-grams, and entropy calculations. The findings presented here are of interest to researchers in the fields of natural language understanding, text processing and compression, speech synthesis and recognition as well as error detection and correction. The results are interesting because they encompass the complete range of hierarchic text patterns (i.e. letters, n-grams (or sub-word patterns) and words).

关键词： n-Grams text analysis Word frequencies Entropy of language Natural language 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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Comprehending consistent and inconsistent causal text sequences: A construction-integration analysis

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DISCOURSE PROCESSES 1996年第1期21卷 1-21页

作者： Singer, M UNIV MANITOBA DEPT PSYCHOLWINNIPEGMB R3T 2N2CANADA

A construction-integration analysis of the comprehension of causal text sequences was performed. According to the validation analysis, the comprehension of both consistent and inconsistent causal sequences requires that tentative bridging inferences be validated with reference to relevant knowledge. Consistent with this proposal, Singer (1993) reported that people needed less time to answer questions about the hypothesized validating facts after consistent and inconsistent sequences than after control, temporal sequences. The construction-integration analysis of these effects focused particularly on a central configuration of causally related propositions. The simulations adopted the following assumptions and parameters: (a) There was a working memory buffer size of 1;(b) all link strengths had an absolute value of 1;and (c) the representations included text base and situation model elements, but no surface elements. Sixteen preliminary simulations, applied to 2 text frames each, influenced decisions concerning 4 simulation choice points. The full simulation was performed for six randomly selected texts from Singer's (1993) experiments. The results revealed a good qualitative fit between the construction-integration activation of the probe questions and their corresponding answer times. In particular, high activation was associated with fast answer time.

关键词： Causal Models Cognitive Processes Higher Education Influences Integration Studies Reading Comprehension Reading Research Simulation text StructureCognitive Research text patterns text Processing (Reading)

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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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An analysis of stylistic variables in electronic mail

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JOURNAL OF BUSINESS AND TECHNICAL COMMUNICATION 1997年第1期11卷 5-23页

作者： Rice, RP USAF ACAD COLORADO SPRINGSCO 80840 USA

This article presents the results of a stylistic analysis of 200 samples of electronic mail memorandums gathered from four organizations. Through systematic counting of textual features such as sentence and paragraph length, grammatical types of sentences, sentence openers, and diction, the study examines patterns of rhetorical choice common to electronic mad. In this sample, writers combined elements of formal and informal discourse but preferred simple coordinate sentence patterns, brief paragraphs, and active verbs. Additionally the serial structuring of message content and reluctance to coordinate and subordinate ideas into appropriate rhetorical patterns indicate a general inattentiveness to providing logical frameworks for readers.

关键词： Discourse Analysis Electronic Mail Organizational Communication Rhetorical Invention Writing ResearchRhetorical Strategies text Factors Writing Style text patterns Stylistics

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