Text Summarization Using Natural Language Processing

Single Document Summarization Using Natural Language Processing

The need for text summarization is crucial as we enter the era of information overload. However, the current implementations are specific to a domain or a genre of the source document. In this paper, we discuss an algorithm for text summarization which is independent of domain and document source. This algorithm creates text summaries by analyzing the logical structure of the sentences. Sentenc...

Text Summarization Using Cuckoo Search Optimization Algorithm

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extr...

EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

Due to the explosive growth of the world-wide web, automatictext summarization has become an essential tool for web users. In this paperwe present a novel approach for creating text summaries. Using fuzzy logicand word-net, our model extracts the most relevant sentences from an originaldocument. The approach utilizes fuzzy measures and inference on theextracted textual information from the docu...

Web Text Corpus for Natural Language Processing

Web text has been successfully used as training data for many NLP applications. While most previous work accesses web text through search engine hit counts, we created a Web Corpus by downloading web pages to create a topic-diverse collection of 10 billion words of English. We show that for context-sensitive spelling correction the Web Corpus results are better than using a search engine. For t...

Natural Language Processing and Text Mining