Generally the searcher either searches for exact information based on the query or just surf topics which interest them on websites. Naturally, when user enters a query related to some topics, they did not get exact result of what they want. If the system selected the relevant passages, grouping together, made it summarizing and fluently, and returned the resulting text it will be an advantage to the user. Otherwise, if the resulting summary is not relevant enough to searcher, the user can

more »

... e the query. Thus, as a result, summarization is used as a technique for improving querying. To ensure this technique they proposed to summarize the content of a temporal topic in existing work by using an anatomy based summarization method called Topic Summarization and Content Anatomy (TSCAN). A temporal similarity (TS) function is implemented to generate the event dependencies and context similarity to form an evolution graph of the topic search. In this paper, we are combining two methods for topic summarization. The first method is mainly based on termfrequency, while the second method is based on ontology. We will construct an ontology database for analyzing the main topics of the article using NPL tool.