PhD Thesis Proposal - Public Lecture - GuanDong Zhang
Room: 248
Title: Analyze and judge Answers/Questions in Text Mining
Abstract:
We are living in an age of information. Texts or documents are main materials to store information. Answers are main examples of texts or documents. However, the amount of Answers is sometimes so huge that we cannot spend enough time to read all answers. Therefore, we usually want to read some related answers. Answer ranking has been regarded as an important assignment when we want to conduct research in the field of the information retrieval. Keywords are important factors in the ranking research since the extraction of keywords is currently considered as an important application to find hidden information. By analyzing keywords, we can find most related.
The main research area of the thesis is on text mining. The research objects are answers. We regard answers to be time series sequences and use Dynamic Time Warping (DTW) to analyze them. Based on DTW, we develop a new model to rank selected answers and apply this model to illustrate CKM data in visualization.
Supervisor: Hao Yu