In order to improve the accuracy of short text similarity calculation, this paper presents the idea that use the history of short text messages to construct semantic feature space, then use the vector in semantic feature space to represent short text and do semantic extension, and finally calculate the short text similarity of corresponding vector in the semantic feature space. This method can ...

In this paper, we explore unsupervised techniques for the task of automatic short answer grading. We compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. Overall...

According to rise of social networking services, short text like micro-blogs has become a valuable resource for practical applications. When using text data in applications, similarity estimation between text is an important process. Conventional methods have assumed that an input text is sufficiently long such that we can rely on statistical approaches, e.g., counting word occurrences. However...

Short text is a popular text form, which is widely used in real-time network news, short commentary, micro-blog and many other fields. With the development of the application such as QQ, mobile phone text messages and movie websites, the size of data is also becoming larger and larger. Most data is useless for us while other data is significant for us. Therefore, it is necessary for us to extra...

Most text mining tasks, including clustering and topic detection, are based on statistical methods that treat text as bags of words. Semantics in the text is largely ignored in the mining process, and mining results often have low interpretability. One particular challenge faced by such approaches lies in short text understanding, as short texts lack enough content from which statistical conclu...