A Maximum Entropy Approach to Natural Language Processing

نویسندگان

  • Adam L. Berger
  • Stephen Della Pietra
  • Vincent J. Della Pietra
چکیده

The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Toward Tweets Normalization Using Maximum Entropy

The use of social network services and microblogs, such as Twitter, has created valuable text resources, which contain extremely noisy text. Twitter messages contain so much noise that it is difficult to use them in natural language processing tasks. This paper presents a new approach using the maximum entropy model for normalizing Tweets. The proposed approach addresses words that are unseen i...

متن کامل

Sequence Modeling with Mixtures of Conditional Maximum Entropy Distributions

We present a novel approach to modeling sequences using mixtures of conditional maximum entropy distributions. Our method generalizes the mixture of first-order Markov models by including the “long-term” dependencies in model components. The “long-term” dependencies are represented by the frequently used in the natural language processing (NLP) domain probabilistic triggers or rules (such as “A...

متن کامل

An Optimal Approach to Local and Global Text Coherence Evaluation Combining Entity-based, Graph-based and Entropy-based Approaches

Text coherence evaluation becomes a vital and lovely task in Natural Language Processing subfields, such as text summarization, question answering, text generation and machine translation. Existing methods like entity-based and graph-based models are engaging with nouns and noun phrases change role in sequential sentences within short part of a text. They even have limitations in global coheren...

متن کامل

Maximum Entropy Model for Punctuat

In this paper we develop a maximum-entropy based method for annotating spontaneous conversational speech with punctuation. The goal of this task is to make automatic transcriptions more readable by humans, and to render them into a form that is useful for subsequent natural language processing and discourse analysis. Our basic approach is to view the insertion of punctuation as a form of taggin...

متن کامل

A Maximum Entropy Approach to Kannada Part Of Speech Tagging

Part Of Speech (POS) tagging is the most important pre-processing step in almost all Natural Language Processing (NLP) applications. It is defined as the process of classifying each word in a text with its appropriate part of speech. In this paper, the probabilistic classifier technique of Maximum Entropy model is experimented for the tagging of Kannada sentences. Kannada language is agglutinat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Computational Linguistics

دوره 22  شماره 

صفحات  -

تاریخ انتشار 1996