The goal of topic-oriented text summarization is to produce informative short description according to the given topic or query. This is somewhat similar to the target of question answering which retrieves exact answers from large text collections. In this paper, we present a lightweight and rule-free summarization technique.
Our method relies on a two-pass re-ranking framework. The first pass is to order the concepts which were clustered via conventional top-down clustering algorithm. The second pass generates the representative sentences from the top N concepts.
The main advantage of our work is that we do not need to build external knowledge or pre-defined rules. This is our first time to participate in DUC. Although the result of our system is not comparable with most top-performed methods, the light-weight and rule free techniques still encourage us to further improve via integrating rich sources.
Operating System : Windows XP
Languages : Java 1.6
Tools : Net Beans/ Eclipse
Processor : 600 MHz or above.
RAM (SD/DDR) : 256 MB
Hard Disc : 30GB