现代电子技术2017，Vol.40Issue(5)：33-37,5.DOI:10.16652/j.issn.1004-373x.2017.05.009
基于概率图模型的多模态数据联合检索算法
Probabilistic graph model based joint retrieval algorithm for multi-modal data
摘要
Abstract
In order to improve the performance of the multi-modal retrieval,a semantic generation model of the multi-modal document and a joint retrieval algorithm for multi-modal data based on this model are proposed. The semantic generation model of the multi-modal document deems that the data of each modal in the document is generated by the same semantic concept, and the documents complies with the joint distribution of data of multiple modals. In order to simplify the solving process of model, the conditional probability of each modal can be calculated independently if assuming that the generation processes among all the modals′ data are mutual independent. During the multi-modal joint retrieval,the joint probability of the query data and the document under retrieval are calculated to obtain the similarity between them. The experimental results show that this algorithm has better retrieval performance than the two-step retrieval algorithm,semantic indexing algorithm and ranking learning algo-rithm. In addition,the algorithm can be applied to the document joint retrieval of data with three and more modals.关键词
多模态检索/概率图模型/极大似然估计/产生式模型Key words
multi-modal retrieval/probabilistic graph model/maximum likelihood estimation/generative model分类
信息技术与安全科学引用本文复制引用
甘胜江,孙连海,何俊林,卢颖..基于概率图模型的多模态数据联合检索算法[J].现代电子技术,2017,40(5):33-37,5.基金项目
中国博士后科学基金面上项目(2014M560730) （2014M560730）
四川省科技厅应用基础项目(2015JY0071) （2015JY0071）
成都师范学院高层次引进人才专项科研项目(YJRC2014-9) （YJRC2014-9）
成都师范学院自然科学类培育项目(CS14ZD02) （CS14ZD02）
