Titlebook: Linguistic Resources for Natural Language Processing; On the Necessity of Max Silberztein Book 2024 The Editor(s) (if applicable) and The

FORAY

書目名稱Linguistic Resources for Natural Language Processing影響因子(影響力)




書目名稱Linguistic Resources for Natural Language Processing影響因子(影響力)學(xué)科排名




書目名稱Linguistic Resources for Natural Language Processing網(wǎng)絡(luò)公開度




書目名稱Linguistic Resources for Natural Language Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Linguistic Resources for Natural Language Processing被引頻次




書目名稱Linguistic Resources for Natural Language Processing被引頻次學(xué)科排名




書目名稱Linguistic Resources for Natural Language Processing年度引用




書目名稱Linguistic Resources for Natural Language Processing年度引用學(xué)科排名




書目名稱Linguistic Resources for Natural Language Processing讀者反饋




書目名稱Linguistic Resources for Natural Language Processing讀者反饋學(xué)科排名

河潭

Formalization of the Quechua Morphologyventory of all Quechua suffixes, I classified them into specific sets corresponding to their POS category. Next, I formalized their grammatical behavior separately, using elementary matrices. The resulting tables describe valid combinations of two, three, and four suffixes. Finally, I formalized the inflection and derivation of each POS category.

COUCH

asthma

The Limitations of Corpus-Based Methods in NLPs. Next, I examine the principles which are at the basis of corpus-based methods and uncover their linguistic naiveté. I finally dispute the scientific validity of empirical approaches. I propose solutions to various problems that are based on the use of carefully handcrafted linguistic methods and resources.

kidney

不成比例

A Polylectal Linguistic Resource for Rromanirammar that describes agglutination. It can be used both for Rromani language studies and for developing Natural Language Processing (NLP) applications. We show that the same architecture can describe other low-resource languages.

interference

不給啤

Linguistic Resources and Methods for Belarusian Natural Language Processing for computational processing of textual information and speech. The proposed resources are also used to collect targeted thematic content to develop and refine natural language processing systems for Belarusian. As a consequence, we show that linguistic resources have not lost their relevance to NLP.

樂章

A New Set of Linguistic Resources for Ukrainiancial sciences to analyze their own corpora of Ukrainian texts. We will first review the various existing NLP software applications that can process Ukrainian texts, their functionalities, and their performance. We then describe the linguistic resources we have developed, and finally compare the results produced by both approaches.

吸氣

The Challenging Task of Translating the Language of Tangoof translating a Tango song lyrics to English. We look at the translations produced by Google Translator and DeepL and we compare them with translations produced by accessing handcrafted linguistic resources specifically developed for Rioplatense Spanish.