✦ LIBER ✦

Augmenting Naive Bayes Classifiers with Statistical Language Models

✍ Scribed by Fuchun Peng; Dale Schuurmans; Shaojun Wang

Book ID: 111587335
Publisher: Springer Netherlands
Year: 2004
Tongue: English
Weight: 153 KB
Volume: 7
Category: Article
ISSN: 1386-4564
DOI: 10.1023/b:inrt.0000011209.19643.e2

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Predicting reading difficulty with stati

Predicting reading difficulty with statistical language models

✍ Kevyn Collins-Thompson; Jamie Callan 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 373 KB

## Abstract A potentially useful feature of information retrieval systems for students is the ability to identify documents that not only are relevant to the query but also match the student's reading level. Manually obtaining an estimate of reading difficulty for each document is not feasible for

Dynamic Web log session identification w

Dynamic Web log session identification with statistical language models

✍ Xiangji Huang; Fuchun Peng; Aijun An; Dale Schuurmans 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 687 KB

Statistical language modeling with a cla

Statistical language modeling with a class-basedn-multigram model

✍ Sabine Deligne; Yoshinori Sagisaka 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 166 KB

In this paper, we present a stochastic language-modeling tool which aims at retrieving variable-length phrases (multigrams), assuming n-gram dependencies between them, hence the name of the model: n-multigram. The estimation of the probability distribution of the phrases is intermixed with a phrase-

[Lecture Notes in Computer Science] Arti

[Lecture Notes in Computer Science] Artificial Neural Networks – ICANN 2006 Volume 4131 || A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis

✍ Kollias, Stefanos D.; Stafylopatis, Andreas; Duch, Włodzisław; Oja, Erkki 📂 Article 📅 2006 🏛 Springer Berlin Heidelberg ⚖ 401 KB