Methodology for Evaluating Citation Parsing and Matching

Fedoryszak, Mateusz; Bolikowski, Łukasz; Tkaczyk, Dominika; Wojciechowski, Krzysztof

doi:10.1007/978-3-642-35647-6_11

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…This is in addition to different ways to abbreviate journal names and nonstandard uses of punctuation marks. These factors made it difficult to use citation parsing software (assuming the results will not be reliable and will need further manual confirmation) and necessitated the tedious task of manual extraction of journal names (Fedoryszak et al, 2013). Finally, journal names could be identified within 33,216 citations to journal articles.…”

Section: Disambiguation Of Npl Citationsmentioning

confidence: 99%

Does open access to academic research help small, science-based companies?

ElSabry¹,

Sumikura

2020

JIUC

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PurposeThis study investigates the extent to which a company's usage of open access (OA) literature for R&D activities depends on its size. The authors’ assumption is that smaller pharmaceutical companies have less access to (usually expensive) journal subscriptions.Design/methodology/approachA fixed-effect Poisson model was used to study a panel dataset of USPTO pharmaceutical company patents. The dependent variable is the count of citations to OA resources in a given company patent.FindingsResults support current anecdotal evidence that many SMEs suffer from high journal prices.Originality/valueThis result justifies the assumption made by policymakers about the potentially positive impact OA mandates have on national innovation activity. It was also shown that collaborating with universities can be a potential coping mechanism for companies that struggle to gain access to the journals they need. In addition to the novelty of its findings, this study introduces a new way to study the impact of OA in nonacademic contexts.

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Section: Disambiguation Of Npl Citationsmentioning

confidence: 99%

Does open access to academic research help small, science-based companies?

ElSabry¹,

Sumikura

2020

JIUC

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“…From the very beginning the main afford in CoAnSys have been put on document analysis algorithms, i.e. author name disambiguation [7,8,9], metadata extraction [10], document similarity and classification calculations [11,12], citation matching [13,14], etc. Some of algorithms can be used in Hadoop environment out-of-box, some need further amendments and some are entirely not applicable [15].…”

Section: Well-suited Algorithmsmentioning

confidence: 99%

Taming the zoo - about algorithms implementation in the ecosystem of Apache Hadoop

Dendek¹,

Czeczko²,

Fedoryszak³

et al. 2013

Preprint

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Content Analysis System (CoAnSys) is a research framework for mining scientific publications using Apache Hadoop. This article describes the algorithms currently implemented in CoAnSys including classification, categorization and citation matching of scientific publications. The size of the input data classifies these algorithms in the range of big data problems, which can be efficiently solved on Hadoop clusters.

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“…indexes of ERNIE data that can facilitate user searches that return informative, ranked, and scored query results and is the basis for a process that takes advantage of indexed Web of Science publications in ERNIE. A similar approach has been described for citation matching of raw text strings [28]. In our process, a text file containing references is passed as input 120 to a Python script.…”

Section: Introductionmentioning

confidence: 99%