Nehodí se? Vůbec nevadí! Zboží můžete vrátit až do 30 dní
S dárkovým poukazem nešlápnete vedle. Obdarovaný si za dárkový poukaz může vybrat cokoliv z naší nabídky.
Až 30 dní na vrácení zboží
Plagiarism is a widely spread problem that is the main focus of interest these days. The main objective of this work is the application of Latent Semantic Analysis (LSA) framework in the field of written-text plagiarism detection. This particular field faces various issues that are discussed thoroughly. In order to infer the latent semantics from the given text, Singular Value Decomposition (SVD) is employed for the purpose of large statistical computations. To overcome issues connected with a large amount of extracted N-grams from the text, a feature selection and subsequently a random indexing techniques are applied. Moreover, this thesis deals with the influence of text pre-processing on the accuracy of plagiarism detection. Simultaneously, the aspects of multilingual environment are explored. Various approaches in common use are discussed and compared with the new proposed method.
Ahoj! Jsem Libroamiko, tvůj knižní rádce.
Jak ti můžu pomoct?