Reviewing Research Trends:A Scientometric Approach Using Gunshot Residue (GSR) Literature as an Example

The ability to manage, distil and disseminate the significant amount of information that is available from published literature is fast becoming a core and critical skill across all research domains, including that of forensic science. In this study, a simplified scientometric approach has been applied to available literature on gunshot residue (GSR) as a test evidence type aiming to evaluate publication trends and explore the interconnectivity between authors. A total of 731 publications were retrieved using the search engine ‘Scopus’ and come from 1589 known authors, of whom 401 contributed to more than one research output on this subject. Out of the total number of publications, only 35 (4.8%) were found to be Open Access (OA). The Compound Annual Growth Rate (CAGR) for years 2006 and 2016 reveals a much higher growth in publications relating to GSR (8.0%) than the benchmark annual growth rate of 3.9%. The distribution of a broad spectrum of keywords generated from the publications confirms a historical trend, in particular regarding the use of analytical techniques, in the study of gunshot residue. The results inform how relevant information extracted from a bibliometric search can be used to explore, analyse and define new research areas

Figure Text Extraction in Biomedical Literature

Background: Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engin

Lost in PubMed: factors influencing the success of medical information retrieval

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Tigrigna language spellchecker and correction system for mobile phone devices

This paper presents on the implementation of spellchecker and corrector system in mobile phone devices, such as a smartphone for the low-resourced Tigrigna language. Designing and developing a spell checking for Tigrigna language is a challenging task. Tigrigna script has more than 32 base letters with seven vowels each. Every first letter has six suffixes. Word formation in Tigrigna depends mainly on root-and-pattern morphology and exhibits prefixes, suffixes, and infixes. A few project have been done on Tigrigna spellchecker on desktop application and the nature of Ethiopic characters. However, in this work we have proposed a systems modeling for Tigrigna language spellchecker, detecting and correction: a corpus of 430,379 Tigrigna words has been used. To indication the validity of the spellchecker and corrector model and algorithm designed, a prototype is developed. The experiment is tested and accuracy of the prototype for Tigrigna spellchecker and correction system for mobile phone devices achieved 92%. This experiment result shows clearly that the system model is efficient in spellchecking and correcting relevant suggested correct words and reduces the misspelled input words for writing Tigrigna words on mobile phone devices

Information retrieval and text mining technologies for chemistry

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio

“More than Meets the Eye” - Analyzing the Success of User Queries in Oria

Discovery systems allow academic library users to locate a wider range of resources than previous OPACs. However, actual usage of these systems may still be challenging. The main aim of this research is to get a better understanding of the hurdles users face while searching contemporary library systems.This study utilizes a transaction log analysis approach, using popular and zero result queries datasets gathered from the statistics module of a library discovery system. It explores what types of queries users perform, how successful the queries are, and examines underlying reasons for unsuccessful queries. To our knowledge, this is the first academic paper to use data originating from built-in transaction logs of the Oria library discovery system.The analysis shows that queries are often curriculum-related: we could pinpoint a relation with curriculum for 58% of the popular queries, and 28% for the zero result searches. A vast majority of popular queries refer to books, databases and journals, and over half of the queries used the title to locate a resource. 20% of the popular queries turned out to be unsuccessful. Zero result queries typically involve long queries, and in many cases consist of pasted reference citations.Our conclusion is that the examined discovery system is rather sensitive. Whilst this suggests the importance of increasing users' information search skills, it also points to the need for enhancing discovery systems and their underlying metadata. Furthermore, due to the prominence of curriculum-related queries, a better integration of curriculum materials ought to be achieved