|
| |
|
|
The evaluation of properties of fine aggregate for asphalt mixtures
Kadlček, Jakub ; Sychra, Martin (referee) ; Dašek, Ondřej (advisor)
The diploma thesis is focused on evaluation of properties of fine aggregate by means of laboratory tests. Fine aggregate evaluation was performed using sieving test, laser diffraction, delta ring and ball test, bitumen number test, uncompacted void content of fine aggregate according to AASHTO T 304, voids of dry compacted filler (Rigden) test and particle density of filler. Laboratory research has led to the discovery of some properties of fine aggregate and their dependencies.
|
|
|
Sentiment Analysis with Use of Data Mining
Sychra, Martin ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
The theme of the work is sentiment analysis, especially in terms of informatics (marginally from a linguistic point of view). The linguistic part discusses the term sentiment and language methods for its analysis, e.g. lemmatization, POS tagging, using the list of stopwords etc. More attention is paid to the structure of the sentiment analyzer which is based on some of the machine learning methods (support vector machines, Naive Bayes and maximum entropy classification). On the basis of the theoretical background, a functional analyzer is projected and implemented. The experiments are focused mainly on comparing the classification methods and on the benefits of using the individual preprocessing methods. The success rate of the constructed classifier reaches up to 84 % in the cross-validation.
|
|
| |
|
|
Entity Knowledge Base Creation from Czech Wikipedia
Sychra, Martin ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to propose and implement a system for an automatic extraction of named entities from Czech Wikipedia, to create a knowledge base consisting of these entities and to evaluate results of the created system. The first part explains basic notions of this field and discusses related work. The main part proposes several methods of extraction and details their implementation. The following types of entities are extracted: people, places, events and organizations. The final part of the thesis presents results, i.e., the success of the individual methods for each entity type and statistics on extraction of the individual entities in the whole Czech Wikipedia context.
|
|
|
The evaluation of properties of fine aggregate for asphalt mixtures
Kadlček, Jakub ; Sychra, Martin (referee) ; Dašek, Ondřej (advisor)
The diploma thesis is focused on evaluation of properties of fine aggregate by means of laboratory tests. Fine aggregate evaluation was performed using sieving test, laser diffraction, delta ring and ball test, bitumen number test, uncompacted void content of fine aggregate according to AASHTO T 304, voids of dry compacted filler (Rigden) test and particle density of filler. Laboratory research has led to the discovery of some properties of fine aggregate and their dependencies.
|
|
|
Sentiment Analysis with Use of Data Mining
Sychra, Martin ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
The theme of the work is sentiment analysis, especially in terms of informatics (marginally from a linguistic point of view). The linguistic part discusses the term sentiment and language methods for its analysis, e.g. lemmatization, POS tagging, using the list of stopwords etc. More attention is paid to the structure of the sentiment analyzer which is based on some of the machine learning methods (support vector machines, Naive Bayes and maximum entropy classification). On the basis of the theoretical background, a functional analyzer is projected and implemented. The experiments are focused mainly on comparing the classification methods and on the benefits of using the individual preprocessing methods. The success rate of the constructed classifier reaches up to 84 % in the cross-validation.
|
|
| |
|
|
Entity Knowledge Base Creation from Czech Wikipedia
Sychra, Martin ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to propose and implement a system for an automatic extraction of named entities from Czech Wikipedia, to create a knowledge base consisting of these entities and to evaluate results of the created system. The first part explains basic notions of this field and discusses related work. The main part proposes several methods of extraction and details their implementation. The following types of entities are extracted: people, places, events and organizations. The final part of the thesis presents results, i.e., the success of the individual methods for each entity type and statistics on extraction of the individual entities in the whole Czech Wikipedia context.
|
|
| |
guest ::
RSS feed.