Networks and Natural Language Processing
نویسندگان
چکیده
Over the last few years, a number of areas of natural language processing have begun applying graph-based techniques. These include, among others, text summarization, syntactic parsing, word sense disambiguation, ontology construction, sentiment and subjectivity analysis, text clustering. In this paper, we present some of the most successful graph-based representations and algorithms used in language processing, and try to explain how and why they work.
منابع مشابه
Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks
Thermal processing of the key lime juice leads to the inactivation of pectin methylesterase (PME) and the degradation of ascorbic acid (AA). These changes affect directly the cloud stability and color of the juice. In this study, an artificial neural network (ANN) model was applied for designing and developing an intelligent system for prediction of the thermal processing effects on the physico...
متن کاملA Primer on Neural Network Models for Natural Language Processing
Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natura...
متن کاملPredictive Control of Gas Injection in Natural Gas Transport Networks
The present sought to draw a comparison between Model Predictive Control performance and two other controllers named Simple PI and Selective PI in controlling large-scale natural gas transport networks. A nonlinear dynamic model of representative gas pipeline was derived from pipeline governing rules and simulated in SIMULINK® environment of MATLAB®. Control schemes were designed to provide a s...
متن کاملUsing Natural Language Processing to Improve Document Categorization with Associative Networks
Associative networks are a connectionist language model with the ability to handle large sets of documents. In this research we investigated the use of natural language processing techniques (part-of-speech tagging and parsing) in combination with Associative Networks for document categorization and compare the results to a TF-IDF baseline. By filtering out unwanted observations and preselectin...
متن کاملUsing Generalized Language Model for Question Matching
Question and answering service is one of the popular services in the World Wide Web. The main goal of these services is to finding the best answer for user's input question as quick as possible. In order to achieve this aim, most of these use new techniques foe question matching. . We have a lot of question and answering services in Persian web, so it seems that developing a question matching m...
متن کاملStatistical Physics for Natural Language Processing
In this paper we study the Enertex model that has been applied to fundamental tasks in Natural Language Processing (NLP) including automatic document summarization and topic segmentation. The model is language independent. It is based on the intuitive concept of Textual Energy, inspired by Neural Networks and Statistical Physics of magnetic systems. It can be implemented using simple matrix ope...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- AI Magazine
دوره 29 شماره
صفحات -
تاریخ انتشار 2008