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Identifying idiolect in forensic authorship attribution: an n-gram textbite approach
No full textForensic authorship attribution is concerned with identifying authors of disputed or anonymous documents, which are potentially evidential in legal cases, through the analysis of linguistic clues left behind by writers. The forensic linguist “approaches this problem of questioned authorship from the theoretical position that every native speaker has their own distinct and individual version of the language [. . . ], their own idiolect” (Coulthard, 2004: 31). However, given the diXculty in empirically substantiating a theory of idiolect, there is growing concern in the Veld that it remains too abstract to be of practical use (Kredens, 2002; Grant, 2010; Turell, 2010). Stylistic, corpus, and computational approaches to text, however, are able to identify repeated collocational patterns, or n-grams, two to six word chunks of language, similar to the popular notion of soundbites: small segments of no more than a few seconds of speech that journalists are able to recognise as having news value and which characterise the important moments of talk. The soundbite oUers an intriguing parallel for authorship attribution studies, with the following question arising: looking at any set of texts by any author, is it possible to identify ‘n-gram textbites’, small textual segments that characterise that author’s writing, providing DNA-like chunks of identifying material
Unsupervised and supervised term weigthing methods for character n-gram based author categorization
No full textNaiboğlu, H. Selahattin (Dogus Author) -- Kaptıkaçtı, Oğuz (Dogus Author) -- Sardal, E. Cemre (Dogus Author) -- Güran, Aysun (Dogus Author) -- Uysal, Mitat (Dogus Author) -- Conference full title: Joint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014; Adile Sultan Palace Istanbul; Turkey; 14 October 2014 through 16 October 2014Author categorization considers the problem of identifying the author of an anonymous article. The goal of this work is to identify authors of articles by using different character n-gram based representations of documents. The use of character n-gram models is a relatively simple idea, but it turns out to be quite effective in many applications. The most important point in n-gram based methods is how to represent the documents. In this study, several widely used unsupervised and supervised n-gram weighting methods are investigated on a Turkish data corpus in combination with different classification algorithms. Apart from this, the character n-gram based features are compared with some stylistic markers and the evaluation results are shared in detail.Computer and Industrial Engineering, Gaziantep University, Istanbul Commercial University, Journal of Intelligent Manufacturing Systems, Sakarya University, Department of Industrial Engineering
A Multi-Language Comparison of Influences on Author Verification using Character N-Grams
No full textWe create a new multi-language corpus for author verification based on Wikipedia talkpages, and evaluate the influence that differences in topic and time have on character n-gram author profiles. Topic alignment between two texts is found to increase author verification precision, and an authors writing style is found to change over time, but not more significantly after 3 years than after 1 year.Information ArchitectureWISElectrical Engineering, Mathematics and Computer Scienc
N-gram-based author profiles for authorship attribution
No full textWe present a novel method for computer-assisted authorship attribution based on character-level n-gram author profiles, which is motivated by an almost-forgotten, pioneering method in 1976. The existing approaches to automated authorship attribution implicitly build author profiles as vectors of feature weights, as language models, or similar. Our approach is based on byte-level n-grams, it is language independent, and the generated author profiles are limited in size. The effectiveness of the approach and language independence are demonstrated in experiments performed on English, Greek, and Chinese data. The accuracy of the results is at the level of the current state of the art approaches or higher in some cases.
Key words: Authorship attribution, character n-grams, text categorizatio
Using N-gram Analysis for Forensic Author Identification and Text Relatedness
No full textAM Session
Using N-gram Analysis for Forensic Author Identification and Text Relatedness
Carole Chaski, ALIAS Technology LLC and Institute for Linguistic Evidence, Inc, US
Pacific Association for Computational Linguistics N-GRAM-BASED AUTHOR PROFILES FOR AUTHORSHIP ATTRIBUTION
No full textWe present a novel method for computer-assisted authorship attribution based on characterlevel n-gram author profiles, which is motivated by an almost-forgotten, pioneering method in 1976. The existing approaches to automated authorship attribution implicitly build author profiles as vectors of feature weights, as language models, or similar. Our approach is based on byte-level n-grams, it is language independent, and the generated author profiles are limited in size. The effectiveness of the approach and language independence are demonstrated in experiments performed on English, Greek, and Chinese data. The accuracy of the results is at the level of the current state of the art approaches or higher in some cases. Key words: Authorship attribution, character n-grams, text categorization 1
The N-glycan Glycoprotein Deglycosylation Complex (Gpd) from Capnocytophaga canimorsus Deglycosylates Human IgG
No full textAuthor Summary Capnocytophaga canimorsus are Gram-negative bacteria from the normal oral flora of dogs and cats. They cause rare but severe infections in humans that have been bitten or simply licked by a dog or cat. Fulminant septicemia and peripheral gangrene with a high mortality are the most common symptoms. A surprising feature of these bacteria is their capacity to feed by foraging the glycan moieties of glycoproteins from animal cells, including phagocytes. Here we show that C. canimorsus can also deglycosylate human IgGs reinforcing the idea that this property of harvesting host glycoproteins may contribute to pathogenesis. We also unravel the complete deglycosylation system which belongs to a large family of systems devoted to foraging complex glycans, found exclusively in the Capnocytophaga-Flavobacteria-Bacteroides group, and whose archetype is the starch harvesting system Sus. It is the first system devoted to deglycosylation of glycoproteins to be characterized
Impact of pharmacist involvement on the utility of a gram-negative blood culture identification panel on antimicrobial usage
No full textBackground: A rapid molecular diagnostic test (MDT) is a test used to identify several different species of gram-negative bacteria and their genetic resistance markers. However, the impact of rapid MDT has not been established when combined with pharmacist involvement. Objective: To determine the impact of pharmacy involvement on patient outcomes when using rapid MDT. The primary outcome is the time from gram stain result to the first dose of the targeted antibiotic.
Methods: This is a single-center, quasi-experimental, 1-group pretest-posttest design study of patients with gram-negative bacteremia in a community hospital. Hospitalized patients 18 years or older were included if they had a gram-negative blood culture. Patients were excluded if they were discharged or expired prior to culture results. Outcomes were compared between patients prior to and after implementation of the automated MDT. This research was determined to be exempt from institutional review board oversight consistent with West Florida Healthcare and in accordance with institutional policy.
Results: The use of rapid MDT combined with pharmacist intervention resulted in a statistically significant decrease in the time to targeted antibiotic therapy (pre-intervention group, n = 77, 44.8 ± 17.8 hours versus post-intervention group, n= 80, 4.4 ± 5.8 hours; P ≤.001). There was no significant difference found between secondary outcomes. Limitations included small sample size as well as inconsistent documentation. Conclusions: The use of rapid MDT combined with pharmacist intervention resulted in a statistically significant decrease in the time to targeted antibiotic therapy.Journal ArticleFinal article publishe
From Geocaching to Mobile Persuasive Learning:Motivating the Interest in the Life and Work of Danish Author Kaj Munk
No full textThis paper presents some of the initial steps taken towards digital mediation of the cultural heritage related to Danish author Kaj Munk and the impact these steps have had on the ongoing research on persuasive learning
Exploring the minimum bactericidal concentration and time kill kinetics of benzothiophene derivatives in gram-positive bacteria
No full textTo determine the minimum bactericidal concentration (MBC) and confirm minimum inhibitory concentration (MIC) of a benzothiophene derivative (#34) using the microdilution and
macrodilution assay against two gram-positive bacteria, including Staphylococcus aureus and Enterococcus faecalis.
● To explore the time and dose dependence bactericidal/bacteriostatic activity of the compound #34 using time kill assay
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