خط مشی دسترسیدرباره ما
ثبت نامثبت نام
راهنماراهنما
فارسی
ورودورود
صفحه اصلیصفحه اصلی
جستجوی مدارک
تمام متن
منابع دیجیتالی
رکورد قبلیرکورد بعدی
Document Type : Latin Dissertation
Language of Document : English
Record Number : 149895
Doc. No : ET21687
Main Entry : Gideon S. Mann
Title Proper : Multi-Document Statistical Fact Extraction and Fusion
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This dissertation presents original techniques for statistical fact extractionand fusion from multiple documents. Fact extraction, or relationship extraction,is a process where natural language text is scanned to find instances of a predeter-mined class of facts (e.g. birthday(x,y)). A framework for training statistical factextractors from example is used wherein a set of examples and a target model areused to annotate an automatically collected corpus. This annotation is then used t oprovide training data for classifiers (Phrase Conditional Likelihood and Nai've Bayes)or sequence models (Conditional Random Fields).Fact extractors are used in two information retrieval tasks. In questionanswering the set of candidate..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL44868.pdf
Title and statement of responsibility and : Multi-Document Statistical Fact Extraction and Fusion [Thesis]
 
 
 
(در صورت عدم وضوح تصویر اینجا را کلیک نمایید)