Improving search engine results using different machine learning models and tools

Improving search engine results using different machine learning models and tools

The aim of this thesis is to provide viable methods that can be used to improve the return position (RP) of a relevant document when a natural language query (NLQ) is applied by a user. For the purpose of demonstration, we will be using IBM's Watson Discovery Service (WDS) as a search engine t...

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Bibliographic Details
Main Author: Ambaye, Michael
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:eng
Published: 2020
Subjects:
IBM Watson
natural language query
Watson discovery
Tietotekniikka
Mathematical Information Technology
602
tiedonhaku
hakuohjelmat
koneoppiminen
big data
kyselykielet
tiedonhallinta
luonnollinen kieli
kieli ja kielet
Query
tiedonhakujärjestelmät
information retrieval
search engines
machine learning
query languages
information management
natural language
languages
information retrieval systems
Online Access: https://jyx.jyu.fi/handle/123456789/73119

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