Search Results for "summarization"

...The word segmentation speed reaches about 2 million words per second (tested under mac air), and the accuracy rate can reach more than 96%. At present, it has realized the functions of Chinese word segmentation, Chinese name recognition, user-defined dictionary, keyword extraction, automatic summarization, and keyword tagging. It can be applied to natural language processing and other aspects, and is suitable for various projects that require high word segmentation effects.

The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classification and indexing.

Auto summarization provides a concise summary for a document. In this I present a Statistical approach to addressing the text generation problem in domain-independent, single-document summarization. My thesis Includes salton’s vector space model which divides the sentences into categories which can also be used for summarizing the contents in WebPages.

This project aims to implement in java the following text mining techniques: Text Language Detection, Keywords and keyphrases extraction, Text Classification, Text Clustering, Single or multiple documents Summarization, Plagiarism Detection.

GoldenOrb is a java library under the Apache License V2.0 for correlation, summarization and clustering of text information.

Performs summarization, categorization, key phrase generation,full text indexing and search,part of speech tagging,identification of place and human names in various document format. Latest code is available at http://www.twit88.com/

WebCQ is a continual query system for large-scale Web information monitoring. It tracks various changes to static and dynamic web pages, delivers personalized notifications and summarization with prioritization, and analyzes page structures.

This project aims at providing an implementation of some state-of-the-art techniques for summarizing multi-dimensional data. Multi-dimensional data summarization can effectively support query optimization algorithms and OLAP applications.