Exploiting PLSA model and conditional random field for refining image annotation

This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is constructed to predict a candidate set of annotations with confidence scores, and then model semantic relationship among the candidate annotations by leveraging conditional ran- dom field. In CRF, the confidence scores generated lay the PLSA model and the Fliekr distance be- tween pairwise candidate annotations are considered as local evidences and contextual potentials re- spectively. The novelty of our method mainly lies in two aspects ： exploiting PLSA to predict a candi- date set of annotations with confidence scores as well as CRF to further explore the semantic context among candidate annotations for precise image annotation. To demonstrate the effectiveness of the method proposed in this paper, an experiment is conducted on the standard Corel dataset and its re- sults are ＇compared favorably with several state-of-the-art approaches.

基于产品层次语义的交互式产品设计方法研究

文章探索产品语义视角下的交互式产品设计方法,以解决如何提升用户体验满意度的问题。基于产品符号学和认知语义学理论,构建用户认知与产品层次语义转换理论框架,提出产品层次语义交互设计概念。使用形态、动作分析、感性工学等科学表义方法提取产品语义设计要素,构建基于产品层次语义交互的产品设计流程,包括设定交互情景、明确用户认知、确定要素表达、提炼情感意向、实现方案设计5个步骤,通过老年家用手持吸尘器的设计实例去验证方法的有效性和可行性。