Acknowledgement Entity Recognition in CORD-19 Papers
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Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F_1=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to 50–60% of named entities are actually acknowledged. We further analyze chronological trends of acknowledgement entities in CORD-19 papers. All codes and labeled data are publicly available at https://github.com/lamps-lab/ackextract.Keywords:
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The article discusses some issues of partial acknowledgement of a claim and its legal consequences. It discusses the question of whether a judgement in a case should be given in acknowledgement of the claim if there is partial acknowledgement by the defendant.
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Acknowledgement is the most important part in academic paper. Its function is to express the attitude to others to establish the friendly interrelationship and atmosphere of academics. Comparing to the different cultures, it aims at exploring the similarities and differences of English acknowledgement.
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Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F_1=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to 50–60% of named entities are actually acknowledged. We further analyze chronological trends of acknowledgement entities in CORD-19 papers. All codes and labeled data are publicly available at https://github.com/lamps-lab/ackextract.
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Bibliometrics analysis was conducted on the acknowledgements made by authors in their journal articles that appeared in the printed version of the International Journal of Computer Vision . The study considered the range of six years for the analysis; 2001-2006.Frequency of appearance of the acknowledgement citation was thoroughly assessed and discussed. The results of the study indicate that, 68% of the journal articles contain acknowledgements; and averagely the literature has 2.3 acknowledgements per journal article. The most common category of acknowledgement during the period of the study was the financial support category. The study further reveals that acknowledgement activity is seriously practiced by the scientists in the literature. Keywords: acknowledgement: authors: computer science: bibliometrics
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This article argues that Cavell's key concept of acknowledgement is of great theological significance. Acknowledgement is meant as a particular interpretation of knowledge, which emphasises the personal responsiveness and responsibility to the human other and to the world. As Cavell himself indicates, acknowledgement also overlaps with faith. However, what such acknowledgement of God amounts to, is not yet satisfactorily understood in the growing literature on Cavell. This article argues that Cavell's treatment of confessions (Augustine, Wittgenstein) and acceptance of promise (Luther) provides important clues to a more elaborate understanding of acknowledgement in general, and of acknowledging God in particular.
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This paper proposes a tree-based acknowledge- ment mechanism designed for a reliable application layer multicast, called ATACK. The proposed mechanism divides the group members into a hierarchy of logical acknowledgement domains by a self-organized way, and further builds the acknowledgement tree in terms of hierarchical acknowledgement domains. The expected size of the acknowledgement domain is within some fixed range, which promises the efficient acknowledgement and avoids adjusting acknowledgement domains frequently. In each domain, only a part of group members send acknowledgement messages to the corresponding acknowledgement processor according to the error correlation of the ALM delivery tree. Therefore the proposed acknowledgement mechanism can effectively reduce the related load and improves the acknowledgement performance. DOI: http://dx.doi.org/10.5755/j01.eee.19.10.5909
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This paper discusses qualification and acknowledgement of IT (Information Technology) profesisonals in conceptual terms originated on psychology and sociology of work, and empirical ones originated from three researches: one run among IT Brazilian professionals about acknowledgement; another among graduated in Information Systems, about acknowledgement and qualification; a case study in an IT organization. It is concluded that social professional acknowledgement are not substantial as perceived by that professionals (social status and wages counts on that perception), despite the acknowledgement of work done by them on organizations might be good. On the other hand, required qualifications are not obtained only through regular or technological undergraduate courses, but also through personal effort and technology certifications.
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