在基于文本的视频检索和推荐系统中，视频标题是描述视频内容的必不可少的一个信息来源．然而，人们对视频标题本身的描述能力并没有进行深入的研究．文中根据标题对视频内容的刻画程度将标题的描述能力分为可描述、可理解不可描述和不可理解3 个等级，并把标题描述能力的评估问题作为分类问题来处理．鉴于支持向量机( SVM) 对小样本分类问题有很好的识别效果，使用SVM 作为分类模型．同时，为弥补标题信息的不足，利用视频标题在搜索引擎中的返回结果作为标题的补充信息．采用此方法对汽车领域的5000 个视频标题进行分类，结果表明: 该方法对可描述类视频标题的识别准确率可达84%; 利用标题的搜索结果后，对可描述类和不可理解类标题识别的F 值都提高了3%．

Video titles,which are used to describe video content in the text-based video retrieval and recommendation system,are essential sources of information. However,there are no in-depth researches on the description ability of video titles. In this paper,a method is proposed to evaluate the description ability of titles,in which the description ability is divided into three levels that are respectively describable,incomprehensible and comprehensible but undescribable,and the evaluation of the description ability is considered as a classification problem. Moreover,the support vector machine ( SVM) with high recognition accuracy for small samples is used as the classifier. Besides,in order to fill up the shortage of title information,the search results in the search engine are used as the supplements. Finally,the proposed method is applied to the classification of 5000 automotive video titles. that,with the help of the search results,the F scores increase by 3% for both describable and incomprehensible titles.