基于人物关系的图片搜索系统

Relationship-Based Image Retrieval System

针对传统的采用关键词搜索人物图片的方式在使用查询关系人语句进行查询时不能识别语义的不足,设计并实现了一种基于人物关系的图片搜索系统架构.基于文档共现和句子共现的关系度算法,从新闻语料中挖掘了人物之间潜在的关联关系.创建了人物图片的领域本体库,本体中包含亲属、朋友、同事等共174种具有层级结构的人物关系属性.提供一个面向查询关系人句子的本体库查询接口,首先基于依存关系树的合并规则从依存句法树提取查询关系人语句的关键组成部分,然后基于三元组补全算法转换得到SPARQL语句,接着使用SPARQL查询人物图片本体库,实现语义检索.最后给出实验结果验证系统的可行性和有效性.

Aiming at the deficiency of identify semantic in traditional keyword tosearch characters the way the picture when you use the query statement to query the relationship between people. The paper designs and achieves an image search architecture based on character relationships. We offer an approach to extract the latent relationships between persons from news corpus. Domain ontology library creates pictures of people and in the ontology contains a total of 174 relatives, friends, colleagues and other kinds of character relationship with the hierarchy properties. An ontology-driven query interface for the sentence which provides a query-oriented relationship of one sentence, first We extract the critical component of the query statement for the relative persons which comsolidation rules based on dependency grammar tree from the dependency syntax tree, then generate the SPARQL sentence with the help of triple supplement algorithm, and use SPARQL sentence to query the image ontology library. The semantic retrieval was realized. Finally, the experiment results were given to verify the feasibility and effectiveness.