- Informacje o czasopiśmie
- Pierwsze wydanie
- 30 Mar 2017
- Częstotliwość wydawania
- 4 razy w roku
- Otwarty dostęp
Zakres stron: 1 - 4
- Otwarty dostęp
Zakres stron: 5 - 19
A new point of view in the study of impact is introduced.
Using fundamental theorems in real analysis we study the convergence of well-known impact measures.
We show that pointwise convergence is maintained by all well-known impact bundles (such as the h-, g-, and R-bundle) and that the μ-bundle even maintains uniform convergence. Based on these results, a classification of impact bundles is given.
As for all impact studies, it is just impossible to study all measures in depth.
It is proposed to include convergence properties in the study of impact measures.
This article is the first to present a bundle classification based on convergence properties of impact bundles.
- Pointwise and uniform convergence of impact measures and bundles
- Second Dini theorem
- Arzelà’s theorem
- Bundle classification
- Generalized h- and g-indices
- Otwarty dostęp
A Morphology-Driven Method for Measuring Technology Complementarity: Empirical Study Involving Alzheimer's Disease
Zakres stron: 20 - 48
Measuring the exact technology complementarity between different institutions is necessary to obtain complementary technology resources for R&D cooperation.
This study constructs a morphology-driven method for measuring technology complementarity, taking medical field as an example. First, we calculate semantic similarities between subjects (S and S) and action-objects (AO and AO) based on the Metathesaurus, forming clusters of S and AO based on a semantic similarity matrix. Second, we identify key technology issues and methods based on clusters of S and AO. Third, a technology morphology matrix of several dimensions is constructed using morphology analysis, and the matrix is filled with subjects -action-objects (SAO) structures according to corresponding key technology issues and methods for different institutions. Finally, the technology morphology matrix is used to measure the technology complementarity between different institutions based on SAO.
The improved technology complementarity method based on SAO is more of a supplementary and refined framework for the traditional IPC method.
In future studies we will reprocess and identify the SAO structures which were not in the technology morphology matrix, and find other methods to characterize key technical issues and methods. Furthermore, we will add the comparison between proposed method and traditional and mostly used complementarity measurement method based on industry chain and industry code.
This study takes medical field as an example. The morphology-driven method for measuring technology complementarity can be migrated and applied for any given field.
From the perspective of complementary technology resources, this study develops and tests a more accurate morphology-driven method for technology complementarity measurement.
- Technology complementarity
- SAO structure
- Technology morphology analysis
- Alzheimer's disease
- Otwarty dostęp
Zakres stron: 49 - 70
Patent classification is one of the areas in Intellectual Property Analytics (IPA), and a growing use case since the number of patent applications has been increasing worldwide. We propose using machine learning algorithms to classify Portuguese patents and evaluate the performance of transfer learning methodologies to solve this task.
We applied three different approaches in this paper. First, we used a dataset available by INPI to explore traditional machine learning algorithms and ensemble methods. After preprocessing data by applying TF-IDF, FastText and Doc2Vec, the models were evaluated by cross-validation in 5 folds. In a second approach, we used two different Neural Networks architectures, a Convolutional Neural Network (CNN) and a bi-directional Long Short-Term Memory (BiLSTM). Finally, we used pre-trained BERT, DistilBERT, and ULMFiT models in the third approach.
BERTTimbau, a BERT architecture model pre-trained on a large Portuguese corpus, presented the best results for the task, even though with a performance of only 4% superior to a LinearSVC model using TF-IDF feature engineering.
The dataset was highly imbalanced, as usual in patent applications, so the classes with the lowest samples were expected to present the worst performance. That result happened in some cases, especially in classes with less than 60 training samples.
Patent classification is challenging because of the hierarchical classification system, the context overlap, and the underrepresentation of the classes. However, the final model presented an acceptable performance given the size of the dataset and the task complexity. This model can support the decision and improve the time by proposing a category in the second level of ICP, which is one of the critical phases of the grant patent process.
To our knowledge, the proposed models were never implemented for Portuguese patent classification.
- Natural Language Processing (NLP)
- Patent classification
- Transfer Learning
- Bi-directional Encoder Representations for Transformers (BERT)
- Otwarty dostęp
Implications of Publication Requirements for the Research Output of Ukrainian Academics in Scopus in 1999–2019
Zakres stron: 71 - 93
This article explores the implications of publication requirements for the research output of Ukrainian academics in Scopus in 1999–2019. As such it contributes to the existing body of knowledge on quantitative and qualitative effects of research evaluation policies.
Three metrics were chosen to analyse the implications of publication requirements for the quality of research output: publications in predatory journals, publications in local journals and publications per SNIP quartile from the disciplinary perspective.
Study results highlight, that, firstly, publications of Ukrainian authors in predatory journals rose to 1% in 2019. Secondly, the share of publications in local journals reached the peak of 47.3% in 2015. In 2019 it fell to 31.8%. Thirdly, though the total number of publications has risen dramatically since 2011, but the share of Q3+Q4 has exceeded the share of Q1+Q2. To summarise, the study findings highligh, that research evaluation policies are required to contain not only quantitative but also qualitative criteria.
The study does not explore in detail the effects of a particular type of publication requirements.
The findings of the study have practical implications for policymakers and university managers aimed to develop research evaluation policies.
This paper gains insights into the effects of publication requirements on the research output of Ukrainian academics in Scopus.
- Publication requirements
- Local journals
- Predatory journals