Editorial for the First Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics

The workshop "Mining Scientific Papers: Computational Linguistics and Bibliometrics" (CLBib 2015), co-located with the 15th International Society of Scientometrics and Informetrics Conference (ISSI 2015), brought together researchers in Bibliometrics and Computational Linguistics in order to study the ways Bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing (NLP). The goals of the workshop were to answer questions like: How can we enhance author network analysis and Bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis? This workshop is the first step to foster the reflection on the interdisciplinarity and the benefits that the two disciplines Bibliometrics and Natural Language Processing can drive from it.Comment: 4 pages, Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics at ISSI 201

Mining Scientific Papers for Bibliometrics: a (very) Brief Survey of Methods and Tools

The Open Access movement in scientific publishing and search engines like Google Scholar have made scientific articles more broadly accessible. During the last decade, the availability of scientific papers in full text has become more and more widespread thanks to the growing number of publications on online platforms such as ArXiv and CiteSeer. The efforts to provide articles in machine-readable formats and the rise of Open Access publishing have resulted in a number of standardized formats for scientific papers (such as NLM-JATS, TEI, DocBook). Our aim is to stimulate research at the intersection of Bibliometrics and Computational Linguistics in order to study the ways Bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing.Comment: 2 pages, paper accepted for the 15th International Society of Scientometrics and Informetrics Conference (ISSI

On the composition of scientific abstracts

Purpose Scientific abstracts reproduce only part of the information and the complexity of argumentation in a scientific article. The purpose of this paper provides a first analysis of the similarity between the text of scientific abstracts and the body of articles, using sentences as the basic textual unit. It contributes to the understanding of the structure of abstracts. Design/methodology/approach Using sentence-based similarity metrics, the authors quantify the phenomenon of text re-use in abstracts and examine the positions of the sentences that are similar to sentences in abstracts in the introduction, methods, results and discussion structure, using a corpus of over 85,000 research articles published in the seven Public Library of Science journals. Findings The authors provide evidence that 84 percent of abstract have at least one sentence in common with the body of the paper. Studying the distributions of sentences in the body of the articles that are re-used in abstracts, the authors show that there exists a strong relation between the rhetorical structure of articles and the zones that authors re-use when writing abstracts, with sentences mainly coming from the beginning of the introduction and the end of the conclusion. Originality/value Scientific abstracts contain what is considered by the author(s) as information that best describe documents’ content. This is a first study that examines the relation between the contents of abstracts and the rhetorical structure of scientific articles. The work might provide new insight for improving automatic abstracting tools as well as information retrieval approaches, in which text organization and structure are important features

Categorizations and Annotations of Citation in Research Evaluation

Abstract Scientific evaluation is based for the most part on citation analysis. However, citation is a phenomenon that is not yet well studied. The use of the Contextual Exploration technique that allows the automatic semantic annotation of the relations between authors, gives some of the answers. New bibliosemantic indicators can be considered in order to provide a better perception of citations through the study of semantic categories. The program implementation proposed in this article raises the question of the evaluation of this approach

Small size new silastic drains: life-threatening hypovolemic shock after thoracic surgery associated with a non-functioning chest tube

We report a case of a massive haemothorax following bilateral surgical resection of apical bullae. Occult bleeding was not recognized until the onset of a life-threatening circulatory collapse associated with metabolic acidosis and a fall in haemoglobin level. Using a thoracotomy, large amounts of blood were evacuated from the thoracic cavity and bleeding originating from ruptured pleural adhesion was easily controlled. Thrombotic material with talc particles was found to obstruct the 19-French 4-channel Blake drain. Although this new silastic Blake tube has been recommended in cardiac surgical patients, extending its indication in thoracic surgery, particularly when talc pleurodesis is used, should be questioned given the enhanced postoperative prothrombotic state and risk of drain obstruction. In conclusion, caution should be exercised when new small-sized material is introduced in clinical practice, especially after talc pleurodesis following thoracic surger

The linguistic patterns and rhetorical structure of citation context : an approach using n-grams

Using the full-text corpus of more than 75,000 research articles published by seven PLOS journals, this paper proposes a natural language processing approach for identifying the function of citations. Citation contexts are assigned based on the frequency of n-gram co-occurrences located near the citations. Results show that the most frequent linguistic patterns found in the citation contexts of papers vary according to their location in the IMRaD structure of scientific articles. The presence of negative citations is also dependent on this structure. This methodology offers new perspectives to locate these discursive forms according to the rhetorical structure of scientific articles, and will lead to a better understanding of the use of citations in scientific articles

Quasi-nuclear and quark model baryonium: historical survey

We review ideas and speculations concerning possible bound states or resonances coupled to the nucleon-antinucleon channel.Comment: 7 pages, no figure, Latex with espcrc2.sty, Talk at QCD99, Montpellier, France, July 1999, to appear in the Proceedings, ed. S. Nariso

The antinucleon-nucleon interaction at low energy : annihilation dynamics

The general properties of antiproton-proton annihilation at rest are presented, with special focus on the two-meson final states. The data exhibit remarkable dynamical selection rules : some allowed annihilation modes are suppressed by one order of magnitude with respect to modes of comparable phase-space. Various phenomenological analyses are reviewed, based on microscopic quark dynamics or symmetry considerations. The role of initial- and final-state interaction is also examined.Comment: 128 pages, 49 tables, 27 figure

A Bayesian approach to star-galaxy classification

Star-galaxy classification is one of the most fundamental data-processing tasks in survey astronomy, and a critical starting point for the scientific exploitation of survey data. For bright sources this classification can be done with almost complete reliability, but for the numerous sources close to a survey's detection limit each image encodes only limited morphological information. In this regime, from which many of the new scientific discoveries are likely to come, it is vital to utilise all the available information about a source, both from multiple measurements and also prior knowledge about the star and galaxy populations. It is also more useful and realistic to provide classification probabilities than decisive classifications. All these desiderata can be met by adopting a Bayesian approach to star-galaxy classification, and we develop a very general formalism for doing so. An immediate implication of applying Bayes's theorem to this problem is that it is formally impossible to combine morphological measurements in different bands without using colour information as well; however we develop several approximations that disregard colour information as much as possible. The resultant scheme is applied to data from the UKIRT Infrared Deep Sky Survey (UKIDSS), and tested by comparing the results to deep Sloan Digital Sky Survey (SDSS) Stripe 82 measurements of the same sources. The Bayesian classification probabilities obtained from the UKIDSS data agree well with the deep SDSS classifications both overall (a mismatch rate of 0.022, compared to 0.044 for the UKIDSS pipeline classifier) and close to the UKIDSS detection limit (a mismatch rate of 0.068 compared to 0.075 for the UKIDSS pipeline classifier). The Bayesian formalism developed here can be applied to improve the reliability of any star-galaxy classification schemes based on the measured values of morphology statistics alone.Comment: Accepted 22 November 2010, 19 pages, 17 figure