Alf Nilsen-Børsskog : The Author Chosen by the Language
In: Multiethnica, Band 39
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In: Multiethnica, Band 39
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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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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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
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
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
This article analyses one element of corpus delicti of misappropriation of authorship, criminalised in Lithuanian Criminal Code Article 191 – the object (or the protected good) of a crime. The quality of Lithuanian national regulation and the scope of object of misappropriation of authorship, which affects the qualification of the crime, is evaluated by comparing it with other European Union countries' criminal legal regulation of intellectual property.
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This article analyses one element of corpus delicti of misappropriation of authorship, criminalised in Lithuanian Criminal Code Article 191 – the object (or the protected good) of a crime. The quality of Lithuanian national regulation and the scope of object of misappropriation of authorship, which affects the qualification of the crime, is evaluated by comparing it with other European Union countries' criminal legal regulation of intellectual property.
BASE
This article analyses one element of corpus delicti of misappropriation of authorship, criminalised in Lithuanian Criminal Code Article 191 – the object (or the protected good) of a crime. The quality of Lithuanian national regulation and the scope of object of misappropriation of authorship, which affects the qualification of the crime, is evaluated by comparing it with other European Union countries' criminal legal regulation of intellectual property.
BASE
This article analyses one element of corpus delicti of misappropriation of authorship, criminalised in Lithuanian Criminal Code Article 191 – the object (or the protected good) of a crime. The quality of Lithuanian national regulation and the scope of object of misappropriation of authorship, which affects the qualification of the crime, is evaluated by comparing it with other European Union countries' criminal legal regulation of intellectual property.
BASE
Paper touch upon the problems of criminal policy in Lithuania after 1990. The author concentrates on two aspects of the problem: legislative criminal policy and practical criminal policy. 79 The author investigates the changes in present Penal code of Lithuania and their impact on the practical application of the laws by courts and other criminal justice institutions. The author describes the direction of major alterations of the laws and practical consequences of these changes. The author provides statistical material concerning application of penalties and other forms of sanctions. These data are being compared with the data in other European countries. The author makes conclusions concerning further development of criminal policy.
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Paper touch upon the problems of criminal policy in Lithuania after 1990. The author concentrates on two aspects of the problem: legislative criminal policy and practical criminal policy. 79 The author investigates the changes in present Penal code of Lithuania and their impact on the practical application of the laws by courts and other criminal justice institutions. The author describes the direction of major alterations of the laws and practical consequences of these changes. The author provides statistical material concerning application of penalties and other forms of sanctions. These data are being compared with the data in other European countries. The author makes conclusions concerning further development of criminal policy.
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In the article the author considers urgent problems of Extradition. The study is based on scientific researches in this area and Laws on Extradition in other countries. The article consists of 3 parts. In the first part the author analyses the notion of Extradition. The legal regulation on Extradition is considered in the second part and the problems of conditions and procedures related to Extradition are presented in the third part of the article. The author pays attention to shortcomings of the legal regulation on Extradition in Lithuania and gives the ways of their elimination. At the same time the author grounds the need of passing the National Extradition Act and at the end in the view he gives the scheme of such law.
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In the article the author considers urgent problems of Extradition. The study is based on scientific researches in this area and Laws on Extradition in other countries. The article consists of 3 parts. In the first part the author analyses the notion of Extradition. The legal regulation on Extradition is considered in the second part and the problems of conditions and procedures related to Extradition are presented in the third part of the article. The author pays attention to shortcomings of the legal regulation on Extradition in Lithuania and gives the ways of their elimination. At the same time the author grounds the need of passing the National Extradition Act and at the end in the view he gives the scheme of such law.
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In this final thesis author analyses problematic aspects of legitimate interest as a lawful basis for processing personal data, its conditions of legitimacy and proper application in practice. Therefore, author analyses the purpose of the legitimate interest, the essential conditions of legitimacy for this lawful basis and its exclusivity from other lawful bases for the processing of personal data. Moreover, author provides a definition of legitimate interest as a lawful basis for processing of personal data. Author analyses stages of the assessment of legitimate interests, the most important evaluation criterions and the practical significance of the results. Also, the author presents relevant case law and examines hypothetical situations, reveals the significance of the necessity and the close connection with the principle of data minimization, the meaning of the balancing test and the proportionality of the impact on the legitimate interests and fundamental rights and freedoms of data subjects. In this final thesis legitimate interest was compared with other lawful bases for the processing of personal data in order to reveal the advantages and disadvantages of legitimate interest. Lastly, in this final thesis author presents other insights into the shortcomings of the legitimate interest as a lawful basis, which could have practical implications for data controllers, who are choosing to process personal data on this lawful basis, and for legislators when considering legislative amendments or new legislation.
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