منابع مشابه
Challenges Behind the Data-driven Bulgarian WordNet (BulTreeBank Bulgarian Wordnet)
The paper presents our work towards the simultaneous creation of a data-driven WordNet for Bulgarian and a manually annotated treebank with semantic information. Such an approach requires synchronization of the word senses in both syntactic and lexical resources, without limiting the WordNet senses to the corpus or vice versa. Our strategy focuses on the identification of senses used in BulTree...
متن کاملCoping with Derivation in the Bulgarian Wordnet
The paper motivates a strategy for identification and annotation of derivational relations in the Bulgarian wordnet that aims at coping with the complex morphology of the language in an elegant way. Our method involves transfer of the Princeton WordNet (morpho)semantic relations into the Bulgarian wordnet, at the level of the synset, and further detection of derivational relations between liter...
متن کاملA Data-Driven Dependency Parser for Bulgarian
One of the main motivations for building treebanks is that they facilitate the development of syntactic parsers, by providing realistic data for evaluation as well as inductive learning. In this paper we present what we believe to be the first robust data-driven parser for Bulgarian, trained and evaluated on data from BulTreeBank (Simov et al., 2002). The parser uses dependency-based representa...
متن کاملEnhancing Learning from Imbalanced Classes via Data Preprocessing: A Data-Driven Application in Metabolomics Data Mining
This paper presents a data mining application in metabolomics. It aims at building an enhanced machine learning classifier that can be used for diagnosing cachexia syndrome and identifying its involved biomarkers. To achieve this goal, a data-driven analysis is carried out using a public dataset consisting of 1H-NMR metabolite profile. This dataset suffers from the problem of imbalanced classes...
متن کاملTarget Word Selection Using WordNet and Data-Driven Models in Machine Translation
Collocation information plays an important role in target word selection of machine translation. However, a collocation dictionary fulfills only a limited portion of selection operation because of data sparseness. To resolve the sparseness problem, we proposed a new methodology that selects target words after determining an appropriate collocation class by using a inter-word semantic similarity...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cognitive Studies | Études cognitives
سال: 2018
ISSN: 2392-2397
DOI: 10.11649/cs.1713