Usporedba alata za pretraživanje teksta

master's thesis

• Title (english): Comparison of text search tools
• Author: Petra Mišeta
• Mentor: Mirta Baranović (mentor)
• Committee member: Mirta Baranović (predsjednik povjerenstva)
• Committee member: Boris Vrdoljak (član povjerenstva)
• Committee member: Ljiljana Brkić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-08, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Tema ovog rada je usporedba sustava za fleksibilno pretraživanje teksta Solr i Elasticsearch. U tu svrhu implementiran je sustav koji služi za potporu prodaji proizvoda, a proizvodi su indeksirani koristeći oba alata. Sustavi su uspoređeni u sljedećim kategorijama: konfiguracija i instalacija, analiziranje, tokenizacija i filtriranje podataka, indeksiranje podataka, aplikacijsko programsko sučelje, korisničko sučelje i rad s alatima, mogućnost predmemoriranja, fleksibilno pretraživanje teksta, performanse prilikom izvođenja upita, prilagođenost pojedinim jezicima, dokumentacija alata i otvorenost koda. Prilikom usporedbe navedene su funkcionalnosti izgrađenog sustava i u svakoj kategoriji objašnjeno je koji alat ima prednost i razlog zbog kojeg je alat bolji u toj kategoriji. Na kraju je na temelju rezultata usporedbe odabran Elasticsearch za indeksiranje podataka u svrhu ostvarivanja funkcionalnosti pretrage podataka i filtriranja.

Abstract (english)

The topic of this thesis is comparison of Solr and Elasticsearch, two most popular tools for full text search. Web application that has features of web shop has been implemented to compare tools. Product data are indexed using both tools. Comparison has been made in these categories: configuration and instalation, analysis, tokenization and data filtering, indexing, application programming interface, user interface, caches, flexible data search, performaces during queries execution, language support, documentation and open source. While comparing tools, features of implemented application have been described and at the end of each category the pros and cons of each tool are described. Finally, based on the results of the comparison, Elasticsearch was selected to index the data in order to achieve the functionality of data search and filtering.

• Keywords: Solr; Elasticsearch; indeksiranje; dokumenti; upiti; pretraživanje teksta; analiza; tokeni
• Keywords (english): Solr; Elasticsearch; indexing; documents; queries; text search; analysis; tokens
• Language: croatian
• URN:NBN: urn:nbn:hr:168:509441
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 15:39:27