20.500.12556/RUL-119412 Adaptation of texts to context Prilagoditev besedil kontekstu objave In this thesis we try to develop a methodology that can adapt texts to target publication types using summarization, natural language generation and paraphrasing. The solution is based on key text characteristics that describe different publication types. To examine types such as social media posts, newspaper articles, research articles and official statements, we use three distinct text evaluation metrics: length, text polarity and readability. While altering key text evaluation metrics, we mostly focus on length due to much research that was done in this field (either with summarization or natural language generation). Using paraphrasing we will try to adjust text readability and polarity that describes reader's negative or positive orientation towards the topic. The process of text adaptation will be implemented iteratively. The developed methodology will automatize writing articles that are based on existing articles. The more crucial contribution of this thesis is that we help to gain access of harder works to those that cannot understand the origin texts. V tem diplomskem delu skušamo razviti metodologijo, ki bo znala s pomočjo povzemanja, generiranja naravnega jezika in parafraziranja prilagoditi be\-se\-di\-lo ciljnemu kontekstu objave. Za rešitev problema se najprej osredotočimo na ključne karakteristike, ki določajo obravnavane tipe objav. Za obravnavo štirih razlilčnih tipov, ki so objave na socialnih omrežjih, novice, znanstveni članki in uradne izjave, uporabimo tri karakteristike: dolžino, polarnost besedila in berljivost. Pri spreminjanju ključnih karakteristik se osredotočimo predvsem na dolžino, saj se veliko raziskav nanaša na prilagajanje teksta, bodisi s povzemanjem ali generiranjem naravnega jezika. S pomočjo parafraziranja bomo skušali prilagajati berljivost in polarnost teksta, ki priča o negativni oziroma pozitivni naravnanosti bralca k besedilu. Proces prilagajanja besedil bo potekal iterativno. Razvita metodologija bo avtomatizirala proces pisanja člankov, ki temeljijo na obstoječih delih. Še bolj pomembno pa je, da s tem omogočimo dostop zahtevnejših del tistim, ki jih v prvotni obliki ne razumejo. text adaptation context-aware artificial intelligence text summarization natural language processing prilagajanje besedil kontekstno-odvisen umetna inteligenca procesiranje naravnega jezika true false false Angleški jezik Slovenski jezik Diplomsko delo/naloga 2020-09-08 14:30:00 2020-09-08 14:30:06 2024-02-02 09:40:38 0000-00-00 00:00:00 2020 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 26341 28976643 Zontar_Luka_-_Prilagoditev_besedil_kontekstu_objave.pdf Zontar_Luka_-_Prilagoditev_besedil_kontekstu_objave.pdf 1 75B4D0AF21CD2C9E543536A542C2BC09 3abb59784aaffaf5a69880978bd857baee95a20b21f535a9fc0f2b97975d6957 d22d8f0b-a1b9-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=134123 Fakulteta za računalništvo in informatiko 0 0 0