آزمایشگاه پردازش زبان طبیعی

With the increasing growth of text documents on the Web, choosing the right information in a limited time is difficult. Using tools such as digitizers, this massive amount of information can be managed by generating draft summaries. The ‌ Proposed Summarization ‌method consists of three stages of preprocessing, processing, and summary generation for news texts

۱- Preprocessing Step : This step of its preprocessing stage includes segmentation (detection of the range of sentences and words), the elimination of expressions or verbs, the identification of numerical values and particular names, rooting with the steppe, and extracting the semantic information required from Foreance.

۲- Processing Step : This step at the processing stage is a feature rating for each entry sentence using eight apparent features in the text, and the likelihood and similarity score for each pair of sentences is calculated by applying extracted data from the Forex. Then the sentences are clustered in three main clusters containing the same sentences, related sentences, and sentences.

۳-Final Step : This step in the final stage is generated by selecting sentences from the clusters in either the “feature rating” or “the number of similar and related sentences”.