Klepetalnik za govorni vnos zaužite hrane

diplomsko delo

Tom Aleksander Gornik (Author), Marko Bajec (Mentor)

Abstract

Danes ima uživanje zdrave in uravnotežene prehrane vse večji pomen. Eno izmed ključnih orodji pri doseganju omenjenega cilja je beleženje vrste in količine zaužite hrane. V okviru diplomske naloge najprej predstavimo razvoj klepetalnikov na splošno. Osrednja tema naloge pa je domensko omejeni klepetalnik za govorni vnos zaužite hrane. Osnova za njegovo delovanje je podatkovna baza s skoraj tisoč živili. Z uporabo klepetalnika želimo od uporabnika pridobiti dovolj podatkov, ki nam bodo omogočili identifikacijo živil, ki so bila vključena v posamezen obrok. Pri implementaciji klepetalnika smo uporabili nekaj metod za obdelavo naravnega jezika, kot so lematizacija, kosinusna razdalja, iskanje nizov in Levenshteinova razdalja. Klepetalnik je zmožen sistematično postavljati vprašanja ob nejasnem oz. nepopolnem govornem vnosu. Prototip rešitve je razvit v okolju Java Swing in je na voljo za uporabo na osebnih računalnikih.

Keywords

klepetalnik;obdelava naravnega jezika;računalnik;strojno učenje;umetna inteligenca;lematizacija;hrana;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2019
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[T. Aleksander Gornik]
UDC:	004(043.2)
COBISS:	1538501571
Views:	618
Downloads:	167
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Chatbot for food input
Secondary abstract:	Today the importance of having a healthy, nutritious diet is greater than ever. One of the main tools in achieving this goal is an efficient way to record the meals one has consumed throughout the day. This diploma thesis gives a brief overview of chatbots in general, but focuses on implementing the logic for a domain specific chatbot. The domain is determined by a database containing almost one thousand foods. The goal is to gather enough information from the user to identify the foods consumed during a particular meal. We use natural language processing (NLP) methods such as lemmatisation, cosine distance, string matching and levenshtein distance. The chatbot is also capable of forming systematical questions when the speech input is incomplete or unclear. The prototype of the chatbot is available as a Java Swing Application for personal computers.
Secondary keywords:	chatbot;natural language processing;computer;machine learning;artificial intelligence;lemmatization;food;computer and information science;diploma;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000468
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	38 str.
ID:	11344501