Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in\n Digital Libraries

Scientists always look for the most accurate and relevant answers to their\nqueries in the literature. Traditional scholarly digital libraries list\ndocuments in search results, and therefore are unable to provide precise\nanswers to search queries. In other words, search in digital libraries is\nmetadata search and, if available, full-text search. We present a methodology\nfor improving a faceted search system on structured content by leveraging a\nfederation of scholarly knowledge graphs. We implemented the methodology on top\nof a scholarly knowledge graph. This search system can leverage content from\nthird-party knowledge graphs to improve the exploration of scholarly content. A\nnovelty of our approach is that we use dynamic facets on diverse data types,\nmeaning that facets can change according to the user query. The user can also\nadjust the granularity of dynamic facets. An additional novelty is that we\nleverage third-party knowledge graphs to improve exploring scholarly knowledge.\n