The Closer the Better: Similarity of Publication Pairs at Different Co-Citation Levels

We investigate the similarities of pairs of articles which are co-cited at the different co-citation levels of the journal, article, section, paragraph, sentence and bracket. Our results indicate that textual similarity, intellectual overlap (shared references), author overlap (shared authors), proximity in publication time all rise monotonically as the co-citation level gets lower (from journal to bracket). While the main gain in similarity happens when moving from journal to article co-citation, all level changes entail an increase in similarity, especially section to paragraph and paragraph to sentence/bracket levels. We compare results from four journals over the years 2010-2015: Cell, the European Journal of Operational Research, Physics Letters B and Research Policy, with consistent general outcomes and some interesting differences. Our findings motivate the use of granular co-citation information as defined by meaningful units of text, with implications for, among others, the elaboration of maps of science and the retrieval of scholarly literature

ActiveCite: An interactive system for automatic citation suggestion

Master'sMASTER OF SCIENC

Measuring Patent-Citations of LIS Literature: An analytical study of the Journal Scientometrics

The purpose of this study is to analyse the utility and application of Library and Information Science (LIS) research in patents representing innovations, inventions and new knowledge. With this research, we have tried to bridge a gap between LIS research and patents, which is unavailable to date in the literature. To conduct the study, various patent search databases were used. Data in the form of DOIs were extracted from the Scopus database for the journal Scientometrics and were processed and analysed in visualisation software and spreadsheet software. The findings reveal how industries filing patents derive valuable inputs from LIS research in terms of its utilization, recognition and acceptance. This research paper will enhance the understanding regarding Library and information science, what is its value in Research and Development (R&D). Normally, it is believed that only STEM (Science, Technology, Engineering and Medical) research is fruitful for patents and innovations. The study breaks the glass ceiling as it provides an evidence-based approach to justify the LIS research does play a crucial role in the growth, development and progress of the society through its existence and proven integration with the patents. The findings reveal that LIS research is influencing Patents as they are being cited regularly with the growth in this discipline

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation