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Lietuvos laikinoji vyriausybė: (1941 06 22 - 08 05) ; monografija
In: Lietuviu̜ tauta [N.F.], 5
Lietuviu̜ tautos sukilimas: 1941 m. birželio 22 - 28 d
Engl. Zsfassung u.d.T.: 1941 June uprising
Seimo posėdžių stenogramų tekstynas autorystės nustatymo bei autoriaus profilio sudarymo tyrimams ; Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks
In our paper we present a corpus of transcribed Lithuanian parliamentary speeches. The corpus is prepared in a specific format, appropriate for different authorship identification tasks. The corpus consists of approximately 111 thousand texts (24 million words). Each text matches one parliamentary speech produced during an ordinary session from the period of 7 parliamentary terms starting on March 10, 1990 and ending on December 23, 2013. The texts are grouped into 147 categories corresponding to individual authors, therefore they can be used for authorship attribution tasks; besides, these texts are also grouped according to age, gender and political views, therefore they are also suitable for author profiling tasks. Whereas short texts complicate recognition of author speaking style and are ambiguous in relation to the style of other authors, we incorporated only texts containing not less than 100 words into the corpus. In order to make each category as comprehensive and representative as possible, we included only those authors, who produced speeches at least 200 times. All the texts are lemmatized, morphologically and syntactically annotated, tokenized into the character n-grams. The statistical information of the corpus is also available. We have also demonstrated that the created corpus can be effectively used in authorship attribution and author profiling tasks with supervised machine learning methods. The corpus structure also allows using it with unsupervised machine learning methods and can be used for creation of rule-based methods, as well as in different linguistic analyses.
BASE
Seimo posėdžių stenogramų tekstynas autorystės nustatymo bei autoriaus profilio sudarymo tyrimams ; Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks
In our paper we present a corpus of transcribed Lithuanian parliamentary speeches. The corpus is prepared in a specific format, appropriate for different authorship identification tasks. The corpus consists of approximately 111 thousand texts (24 million words). Each text matches one parliamentary speech produced during an ordinary session from the period of 7 parliamentary terms starting on March 10, 1990 and ending on December 23, 2013. The texts are grouped into 147 categories corresponding to individual authors, therefore they can be used for authorship attribution tasks; besides, these texts are also grouped according to age, gender and political views, therefore they are also suitable for author profiling tasks. Whereas short texts complicate recognition of author speaking style and are ambiguous in relation to the style of other authors, we incorporated only texts containing not less than 100 words into the corpus. In order to make each category as comprehensive and representative as possible, we included only those authors, who produced speeches at least 200 times. All the texts are lemmatized, morphologically and syntactically annotated, tokenized into the character n-grams. The statistical information of the corpus is also available. We have also demonstrated that the created corpus can be effectively used in authorship attribution and author profiling tasks with supervised machine learning methods. The corpus structure also allows using it with unsupervised machine learning methods and can be used for creation of rule-based methods, as well as in different linguistic analyses.
BASE
Seimo posėdžių stenogramų tekstynas autorystės nustatymo bei autoriaus profilio sudarymo tyrimams ; Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks
In our paper we present a corpus of transcribed Lithuanian parliamentary speeches. The corpus is prepared in a specific format, appropriate for different authorship identification tasks. The corpus consists of approximately 111 thousand texts (24 million words). Each text matches one parliamentary speech produced during an ordinary session from the period of 7 parliamentary terms starting on March 10, 1990 and ending on December 23, 2013. The texts are grouped into 147 categories corresponding to individual authors, therefore they can be used for authorship attribution tasks; besides, these texts are also grouped according to age, gender and political views, therefore they are also suitable for author profiling tasks. Whereas short texts complicate recognition of author speaking style and are ambiguous in relation to the style of other authors, we incorporated only texts containing not less than 100 words into the corpus. In order to make each category as comprehensive and representative as possible, we included only those authors, who produced speeches at least 200 times. All the texts are lemmatized, morphologically and syntactically annotated, tokenized into the character n-grams. The statistical information of the corpus is also available. We have also demonstrated that the created corpus can be effectively used in authorship attribution and author profiling tasks with supervised machine learning methods. The corpus structure also allows using it with unsupervised machine learning methods and can be used for creation of rule-based methods, as well as in different linguistic analyses.
BASE
Seimo posėdžių stenogramų tekstynas autorystės nustatymo bei autoriaus profilio sudarymo tyrimams ; Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks
In our paper we present a corpus of transcribed Lithuanian parliamentary speeches. The corpus is prepared in a specific format, appropriate for different authorship identification tasks. The corpus consists of approximately 111 thousand texts (24 million words). Each text matches one parliamentary speech produced during an ordinary session from the period of 7 parliamentary terms starting on March 10, 1990 and ending on December 23, 2013. The texts are grouped into 147 categories corresponding to individual authors, therefore they can be used for authorship attribution tasks; besides, these texts are also grouped according to age, gender and political views, therefore they are also suitable for author profiling tasks. Whereas short texts complicate recognition of author speaking style and are ambiguous in relation to the style of other authors, we incorporated only texts containing not less than 100 words into the corpus. In order to make each category as comprehensive and representative as possible, we included only those authors, who produced speeches at least 200 times. All the texts are lemmatized, morphologically and syntactically annotated, tokenized into the character n-grams. The statistical information of the corpus is also available. We have also demonstrated that the created corpus can be effectively used in authorship attribution and author profiling tasks with supervised machine learning methods. The corpus structure also allows using it with unsupervised machine learning methods and can be used for creation of rule-based methods, as well as in different linguistic analyses.
BASE
Seimo posėdžių stenogramų tekstynas autorystės nustatymo bei autoriaus profilio sudarymo tyrimams ; Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks
In our paper we present a corpus of transcribed Lithuanian parliamentary speeches. The corpus is prepared in a specific format, appropriate for different authorship identification tasks. The corpus consists of approximately 111 thousand texts (24 million words). Each text matches one parliamentary speech produced during an ordinary session from the period of 7 parliamentary terms starting on March 10, 1990 and ending on December 23, 2013. The texts are grouped into 147 categories corresponding to individual authors, therefore they can be used for authorship attribution tasks; besides, these texts are also grouped according to age, gender and political views, therefore they are also suitable for author profiling tasks. Whereas short texts complicate recognition of author speaking style and are ambiguous in relation to the style of other authors, we incorporated only texts containing not less than 100 words into the corpus. In order to make each category as comprehensive and representative as possible, we included only those authors, who produced speeches at least 200 times. All the texts are lemmatized, morphologically and syntactically annotated, tokenized into the character n-grams. The statistical information of the corpus is also available. We have also demonstrated that the created corpus can be effectively used in authorship attribution and author profiling tasks with supervised machine learning methods. The corpus structure also allows using it with unsupervised machine learning methods and can be used for creation of rule-based methods, as well as in different linguistic analyses.
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Tremtis prie Manos upės: skiriama 1948-u̜j̜u̜ gegužės 22-osios Didžiosios lietuviu̜ tremties atminimui ; paroda "Tas nelaimingas Sibiras ...", 2007 m. birželio 14 - 20 d
In: Lietuvos Nacionalinio Muziejaus biblioteka 19
Baudžiamoji atsakomybė už pasikėsinimą padaryti nusikalstamą veiką netiesiogine tyčia – kelias link nuoseklesnės ir pagrįstesnės baudžiamosios politikos? ; Is Criminal Liability for an Attempt with Dolus Eventualis the Way Towards a More Reasonable and a More Consistent Penal Policy?
Furthermore, in order to find out the possible obstacles for the proposal to apply criminal liability for the attempts with dolus eventualis, related norms of the Penal Code as well as the opinions of the researchers of criminal law are analysed. The analysis of Article 22 of the Lithuanian Penal Code shows that the text of the Penal Code does not preclude criminal liability for an attempt with dolus eventualis. What is more, the analysis of the theoretical discussion of the pro and contra views regarding the criminalisation of an attempt with dolus eventualis allows to conclude that dolus eventualis is compatible with the concept of attempt. Consequently, the author ascertains that there are no formal (dogmatic) reasons to object to the criminal liability for an attempt with dolus eventualis. He indicates that the discussion is of penal-political nature. The author concludes that because of the high dangerousness of the crimes committed with dolus eventualis, it is more politicaly reasonable to qualify such crimes according to the rules that are applied for intentional crimes (and, consequently, punish attempts) than to qualify them similarly to negligent crimes (and leave attempts unpunished).
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Baudžiamoji atsakomybė už pasikėsinimą padaryti nusikalstamą veiką netiesiogine tyčia – kelias link nuoseklesnės ir pagrįstesnės baudžiamosios politikos? ; Is Criminal Liability for an Attempt with Dolus Eventualis the Way Towards a More Reasonable and a More Consistent Penal Policy?
Furthermore, in order to find out the possible obstacles for the proposal to apply criminal liability for the attempts with dolus eventualis, related norms of the Penal Code as well as the opinions of the researchers of criminal law are analysed. The analysis of Article 22 of the Lithuanian Penal Code shows that the text of the Penal Code does not preclude criminal liability for an attempt with dolus eventualis. What is more, the analysis of the theoretical discussion of the pro and contra views regarding the criminalisation of an attempt with dolus eventualis allows to conclude that dolus eventualis is compatible with the concept of attempt. Consequently, the author ascertains that there are no formal (dogmatic) reasons to object to the criminal liability for an attempt with dolus eventualis. He indicates that the discussion is of penal-political nature. The author concludes that because of the high dangerousness of the crimes committed with dolus eventualis, it is more politicaly reasonable to qualify such crimes according to the rules that are applied for intentional crimes (and, consequently, punish attempts) than to qualify them similarly to negligent crimes (and leave attempts unpunished).
BASE