基于WordNet和SUMO本体集成的自动语义检索及可视化模型

针对语义检索在实际应用中面临的用户查询意图获取困难、潜在语义索引计算复杂、领域本体覆盖范围小、概念语义类型不丰富、自动化程度低等问题,提出基于WordNet和SUMO本体集成的自动语义检索及可视化模型。实验表明这种模型能够过滤掉大量与用户查询无关的信息,提高信息检索系统的检准率,并很好地满足用户可视化和个性化检索需求。

Automatic Semantic Retrieval and Visualization Model Based on WordNet and SUMO Ontology Integration

There still exists some problems in the practical application of semantic retrieval,such as hardness to acquire user’s query intent,complex computing process of latent semantic index,small area of domain ontology coverage,poor concept semantic types,lower automatic level,etc.Aiming at these problems,this paper puts forward the automatic semantic retrieval and visualization model based on WordNet and SUMO ontology integration.Experiment shows: the proposed model can filter out a large number of information unrelated to user query subject,and not only improve the precision of information retrieval system,but also well satisfy user’s retrieval demand of visualization and individuation.