Deep Learning for Technical Document Classification

In large technology companies, the requirements for managing and organizing technical documents created by engineers and managers have increased dramatically in recent years, which has led to a higher demand for more scalable, accurate, and automated document classification. Prior studies have only focused on processing text for classification, whereas technical documents often contain multimodal information. To leverage multimodal information for document classification to improve the model performance, this paper presents a novel multimodal deep learning architecture, TechDoc, which utilizes three types of information, including natural language texts and descriptive images within documents and the associations among the documents. The architecture synthesizes the convolutional neural network, recurrent neural network, and graph neural network through an integrated training process. We applied the architecture to a large multimodal technical document database and trained the model for classifying documents based on the hierarchical International Patent Classification system. Our results show that TechDoc presents a greater classification accuracy than the unimodal methods and other state-of-the-art benchmarks. The trained model can potentially be scaled to millions of real-world multimodal technical documents, which is useful for data and knowledge management in large technology companies and organizations.Comment: 16 pages, 8 figures, 9 table

The Current and Evolving Landscape of Bibliometric Tools and Technologies

While bibliometrics has been around for decades, with the recent development of new bibliometric tools, there has been a surge in interest in bibliometric services at academic institutions in North America. Navigating this rapidly evolving landscape can be a challenge for academic institutions as they attempt to determine which tools and skill sets will best meet their needs. This issue of Library Technology Reports, “The Current and Evolving Landscape of Bibliometric Tools and Technologies” (vol. 58, no. 8), will help guide decision makers and practitioners in their selection and use of current bibliometric tools and related systems, and it will offer some insight into future directions

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute

Congress UPV Proceedings of the 21ST International Conference on Science and Technology Indicators

This is the book of proceedings of the 21st Science and Technology Indicators Conference that took place in València (Spain) from 14th to 16th of September 2016. The conference theme for this year, ‘Peripheries, frontiers and beyond’ aimed to study the development and use of Science, Technology and Innovation indicators in spaces that have not been the focus of current indicator development, for example, in the Global South, or the Social Sciences and Humanities. The exploration to the margins and beyond proposed by the theme has brought to the STI Conference an interesting array of new contributors from a variety of fields and geographies. This year’s conference had a record 382 registered participants from 40 different countries, including 23 European, 9 American, 4 Asia-Pacific, 4 Africa and Near East. About 26% of participants came from outside of Europe. There were also many participants (17%) from organisations outside academia including governments (8%), businesses (5%), foundations (2%) and international organisations (2%). This is particularly important in a field that is practice-oriented. The chapters of the proceedings attest to the breadth of issues discussed. Infrastructure, benchmarking and use of innovation indicators, societal impact and mission oriented-research, mobility and careers, social sciences and the humanities, participation and culture, gender, and altmetrics, among others. We hope that the diversity of this Conference has fostered productive dialogues and synergistic ideas and made a contribution, small as it may be, to the development and use of indicators that, being more inclusive, will foster a more inclusive and fair world

The waves of Biotechnological Innovation in Medicine

Abstract Improving medicine and health is the ultimate purpose of biotechnological innovation, where basic science is used to develop new innovative diagnostics and therapeutics to significantly improve the lives of patients worldwide. Concurrently, for three stakeholder groups, the primary goal is to generate profitable business from biotechnological innovation. These stakeholders are ‘entrepreneurial’ biotech companies, venture capitalists and established pharmaceutical firms. This dissertation evaluates interfirm cooperation and venture capital investments, aiming to better understand how more biotechnological innovation can reach the market and which biotechnologies will revolutionize R&D productivity and global healthcare. The first studies show that alliances between established pharmaceutical firms and biotech companies outperform acquisitions of biotech companies by such firms, as these acquisition negatively affect innovation performance. Furthermore, alliances involve a risk-return trade-off in new product development, for biotech companies as technology suppliers. Moreover, for big pharma, alliances with- and acquisitions of biotech companies are both complementary innovation activities at higher levels of firms’ absorptive capacity. Regarding venture capital, the final studies show that venture capitalists fulfil a crucial role in the biopharmaceutical value chain. By investing in the right technologies and therapeutic areas, venture capitalists build for big pharma as they foresee big pharma’s future innovation demand. Simultaneously, venture capitalists create a technology push as visionary technological gatekeepers. Finally, the dissertation concludes that big pharma’s dominant logic and blockbuster paradigm have been the root c

Graphs behind data: A network-based approach to model different scenarios

openAl giorno d’oggi, i contesti che possono beneficiare di tecniche di estrazione della conoscenza a partire dai dati grezzi sono aumentati drasticamente. Di conseguenza, la definizione di modelli capaci di rappresentare e gestire dati altamente eterogenei è un argomento di ricerca molto dibattuto in letteratura. In questa tesi, proponiamo una soluzione per affrontare tale problema. In particolare, riteniamo che la teoria dei grafi, e più nello specifico le reti complesse, insieme ai suoi concetti ed approcci, possano rappresentare una valida soluzione. Infatti, noi crediamo che le reti complesse possano costituire un modello unico ed unificante per rappresentare e gestire dati altamente eterogenei. Sulla base di questa premessa, mostriamo come gli stessi concetti ed approcci abbiano la potenzialità di affrontare con successo molti problemi aperti in diversi contesti. ​Nowadays, the amount and variety of scenarios that can benefit from techniques for extracting and managing knowledge from raw data have dramatically increased. As a result, the search for models capable of ensuring the representation and management of highly heterogeneous data is a hot topic in the data science literature. In this thesis, we aim to propose a solution to address this issue. In particular, we believe that graphs, and more specifically complex networks, as well as the concepts and approaches associated with them, can represent a solution to the problem mentioned above. In fact, we believe that they can be a unique and unifying model to uniformly represent and handle extremely heterogeneous data. Based on this premise, we show how the same concepts and/or approach has the potential to address different open issues in different contexts. ​INGEGNERIA DELL'INFORMAZIONEopenVirgili, Luc