Component recommendation for development of composite consumer applications

doctoral thesis

• Title (croatian): Predlaganje komponenata za razvoj kompozitnih potrošačkih primjenskih programa
• Author: Ivan Budiselić
• Mentor: Siniša Srbljić (mentor)
• Committee member: Siniša Srbljić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; (Department of Electronics, Microelectronics, Computer and Intelligent Systems); Zagreb
• Defense date and country: 2014, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing; Architecture of Computer Systems
• Universal decimal classification (UDC): 004 - Computer science and technology. Computing. Data processing

Abstract

Consumer computing is a research area that focuses on methodologies and tools that enable consumers to create their own applications. Consumers create applications by composing existing applications through intuitive actions on their graphical user interfaces. Support for component discovery has been identified as a key challenge in various forms of composite application development, and is especially important in consumer computing. This dissertation introduces a general method for component recommendation based on structural similarity of compositions which dynamically ranks and recommends components as a composite consumer application is being incrementally developed by structurally comparing the partial composition with a database of previously completed compositions. Using this method, four component recommender algorithms are defined. Accuracy, coverage and response time of the presented algorithms are evaluated in detail on a Yahoo Pipes dataset and a synthetic dataset that models more complex composite consumer applications. The results show that the presented approach is effective in addressing the component discovery challenge in consumer computing. The scientific contributions of the doctoral thesis are a set of models for composite application structure, a framework for component recommendation based on composition structural similarity, a set of component recommender algorithms and the evaluation of this proposed set of algorithms on precision, recall, execution time and other recommender success measures.

Abstract (croatian)

Potrošačko računarstvo je istraživačko područje usmjereno prema metodologijama i alatima koji omogućuju potrošačima da stvaraju vlastite primjenske programe. Potrošači stvaraju primjenske programe povezujući postojeće primjenske programe koristeći intuitivne akcije na njihovim grafičkim korisničkim sučeljima. Podrška za otkrivanje komponenata je ključan izazov u raznim okruženjima za razvoj kompozitnih primjenskih programa i posebno je važna u potrošačkom računarstvu. Ova disertacija uvodi općenitu metodu za predlaganje komponenata zasnovano na strukturnoj sličnosti kompozicija koja dinamički rangira i predlaže komponente tijekom postupnog razvoja potrošačkog primjenskog programa uspoređujući djelomičnu kompoziciju s bazom prethodno izgrađenih kompozicija. Koristeći navedenu metodu, definirana su četiri algoritma za predlaganje komponenata. Točnost, pokrivenost kataloga i vrijeme odziva predloženih algoritama vrednovani su na skupu Yahoo Pipes kompozicija i sintetičkom skupu kompozicija koji modelira složenije potrošačke primjenske programe. Rezultati pokazuju da je predloženi pristup prikladan i učinkovit za rješavanje problema otkrivanja komponenata u potrošačkom računarstvu. Znanstveni doprinosi doktorskog rada su skup modela strukture kompozitnih primjenskih programa, radni okvir za preporučivanje komponenata zasnovano na analizi strukturne sličnosti kompozicija, skup algoritama preporučivanja komponenata i vrednovanje predloženog skupa algoritama po preciznosti, odzivu, vremenu izvođenja i drugim mjerama uspješnosti.

• Keywords: consumer computing; component-based systems; component discovery; recommender systems; structural similarity
• Keywords (croatian): potrošačko računarstvo; sustavi zasnovani na komponentama; otkrivanje komponenata; sustavi za predlaganje; strukturna sličnost
• Language: english
• URN:NBN: urn:nbn:hr:168:606119
• Study programme: Title: Electrical Engineering and Computing; Study programme type: university; Study level: postgraduate; Academic / professional title: Doktor znanosti elektrotehnike i računarstva (Doktor znanosti elektrotehnike i računarstva)
• Type of resource: Text
• Extent: 187 str. ; 30 cm.
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-04-19 12:53:36