Semantic Search on Text and Knowledge Bases

Abstract

This article provides a comprehensive overview of the broad area of semantic on text and knowledge bases. In a nutshell, semantic is search with meaning. This meaning can refer to various parts of the process: understanding the query instead of just finding matches of its components in the data, understanding the data instead of just searching it for such matches, or representing knowledge in a way suitable for meaningful retrieval.Semantic is studied in a variety of different communities with a variety of different views of the problem. In this survey, we classify this work according to two dimensions: the type of data text, knowledge bases, combinations of these and the kind of keyword, structured, natural language. We consider all nine combinations. The focus is on fundamental techniques, concrete systems, and benchmarks. The survey also considers advanced issues: ranking, indexing, ontology matching and merging, and inference. It also provides a succinct overview of fundamental natural language processing techniques: POS-tagging, named-entity recognition and disambiguation, sentence parsing, and distributional semantics.The survey is as self-contained as possible, and should thus also serve as a good tutorial for newcomers to this fascinating and highly topical field.