SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
作者：
Highlights：
• Search, select and rank unstructured, structured (relational) and partly structured (NoSQL) data.
• Maps a textual data collection and a semantic knowledge base into a tightly-coupled semantic graph.
• Involves users during semantic index creation, initial query formulation and query refinement.
• Parallelized query processing, with a dedicated model for answer weighting and relevance scoring.
• Comparative experiments with legacy methods highlight solution’s flexibility & effectiveness.
摘要
•Search, select and rank unstructured, structured (relational) and partly structured (NoSQL) data.•Maps a textual data collection and a semantic knowledge base into a tightly-coupled semantic graph.•Involves users during semantic index creation, initial query formulation and query refinement.•Parallelized query processing, with a dedicated model for answer weighting and relevance scoring.•Comparative experiments with legacy methods highlight solution’s flexibility & effectiveness.
论文关键词：Semantic queries,Inverted index,NoSQL indexing,Semantic network,Semantic-aware data processing,Textual databases,Query relaxation,Semantic disambiguation
论文评审过程：Received 5 July 2018, Revised 4 October 2018, Accepted 8 November 2018, Available online 15 November 2018, Version of Record 19 December 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.11.010
