This paper presents a hybrid document recommender system intended for use in digital libraries and institutional repositories that are part of the Slovenian Open Access Infrastructure. The ...recommender system provides recommendations of similar documents across different digital libraries and institutional repositories with the aim to connect researchers and improve collaboration efforts. The hybrid recommender system makes use of document processing techniques, document metadata, and the similarity ranking function BM25 to provide content-based recommendations as a primary method. It also uses collaborative-filtering methods as a secondary method in a cascade hybrid recommendation technique. We also provide a real-world data feedback collection analysis for our hybrid recommender system on an academic digital repository in order to be able to identify suitable time-frames for direct feedback collection during the year.
Prispevek izhaja iz treh izzivov, ki jih zaznavamo pri pouku slovenščine v višjih razredih osnovnih šol in v srednjih šolah: kako odpraviti napake knjižne norme, ki vztrajajo v pisnih izdelkih ...učencev; kako izboljšati frazeološko kompetenco; kako izboljšati sporazumevalno jezikovno zmožnost. Ti izzivi so osrednja točka razvoja sodobnega učnega e-okolja Slovenščina na dlani, ki temelji na jezikovnih in informacijsko-komunikacijskih tehnologijah ter prinaša podporo prožnim oblikam poučevanja, poučevanju na daljavo, lajša učiteljevo delo, omogoča pa tudi motiviranje učencev prek elementov igrifikacije. V prispevku predstavljamo zasnovo in izvedbo vsakega od štirih vsebinskih sklopov e-okolja: pravopis, slovnica, frazeologija in besedila.
The OpenScience Slovenia metadata dataset contains metadata entries for Slovenian public domain academic documents which include undergraduate and postgraduate theses, research and professional ...articles, along with other academic document types. The data within the dataset was collected as a part of the establishment of the Slovenian Open-Access Infrastructure which defined a unified document collection process and cataloguing for universities in Slovenia within the infrastructure repositories. The data was collected from several already established but separate library systems in Slovenia and merged into a single metadata scheme using metadata deduplication and merging techniques. It consists of text and numerical fields, representing attributes that describe documents. These attributes include document titles, keywords, abstracts, typologies, authors, issue years and other identifiers such as URL and UDC. The potential of this dataset lies especially in text mining and text classification tasks and can also be used in development or benchmarking of content-based recommender systems on real-world data.
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