ConceptEVA: Concept-Based Interactive Exploration and Customization of Document Summaries

With the most advanced natural language processing and artificial intelligence approaches, effective summarization of long and multi-topic documents - such as academic papers - for readers from different domains still remains a challenge. To address this, we introduce ConceptEVA, a mixed-initiative approach to generate, evaluate, and...

Recurrent knowledge graph embedding for effective recommendation

Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing methods mainly rely on hand-engineered features from KGs (e.g., meta paths), which requires domain knowledge. This paper presents RKGE, a KG embedding approach that automatically learns semantic representations of both entities and paths between entities...