Docear combines a mind-mapping tool with a recommender system for academic literature and a reference manager. The mind maps allow users to organize their ideas and to import the annotations they made while reading PDFs, e.g., comments, highlights or bookmarks. The software works with standard PDF annotations, thus can be used with different PDF viewers. Read more…

Mr. DLib’s Recommendations as a Service (RaaS) allows operators of academic products to easily integrate a scientific recommender system into their products. The basic idea of Mr. DLib’s scientific recommender system is to calculate recommendations for research articles, call for papers, grants, etc. on Mr. DLib’s server. Operators of academic products may then request recommendations from Mr. DLib and display the recommendations to their users. Read more…

Co-Citation Proximity Analysis (CPA) is a method to compute both local and global instances of semantic similarity in academic documents by examining citation proximity in the full texts of documents. CPA was developed with two applications in mind: recommender systems and clustering. Regarding the first application, an improved measure of document semantic similarity, which computes similarity at a more fine-grained resolution, has the potential to significantly improve the relevance of academic literature recommendations. Read more…

Co-Citation Proximity Analysis (CPA) is a method to compute both local and global instances of semantic similarity in academic documents by examining citation proximity in the full texts of documents. CPA was developed with two applications in mind: recommender systems and clustering. Regarding the first application, an improved measure of document semantic similarity, which computes similarity at a more fine-grained resolution, has the potential to significantly improve the relevance of academic literature recommendations. Read more…