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" St at ist ical machine learning for information retrieval "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 150717
Doc. No : ET22509
Main Entry : Adam Berger
Title Proper : St at ist ical machine learning for information retrieval
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Probably the most important single component of this framework is a parametric sta-tistical model of word relatedness. A longstanding problem in IR has been t o develop amathematically principled model for document processing which acknowledges t h a t one se-quence of words may be closely related t o another even if the pair have few (or no) wordsin common. The fact t h a t a document contains the word automobile, for example, sug-gests t h a t it may be relevant t o the queries Where can I find information on motorvehicles? and Tell me about car transmissions, even though the word automobileitself appears nowhere in these....-...,..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 : TL45730.pdf
Title and statement of responsibility and : St at ist ical machine learning for information retrieval [Thesis]
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TL45730.pdf
TL45730.pdf
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