Semantic information retrieval research based on co-occurrence analysis

Purpose – The paper aims to develop a new method for potential relations retrieval. It aims to find common aspects between co-occurrence analysis and ontology to build a model of semantic information retrieval based on co-occurrence analysis. Design/methodology/approach – This paper used a literature review, co-occurrence analysis, ontology build and other methods to design a model and process of semantic information retrieval based on co-occurrence analysis. Archaeological data from Wuhan University Library’s bibliographic retrieval systems was used for experimental analysis. Findings – The literature review found that semantic information retrieval research mainly concentrates on ontology-based query techniques, semantic annotation and semantic relation retrieval. Moreover most recent systems can only achieve obvious relations retrieval. Ontology and co-occurrence analysis have strong similarities in theoretical ideas, data types, expressions, and applications. Research limitations/implications – The experiment data came from a Chinese university which perhaps limits its usefulness elsewhere. Practical implications – This paper constructed a model to understand potential relations retrieval. An experiment proved the feasibility of co-occurrence analysis used in semantic information retrieval. Compared with traditional retrieval, semantic information retrieval based on co-occurrence analysis is more user-friendly. Originality/value – This study is one of the first to combine co-occurrence analysis with semantic information retrieval to find detailed relationships.