Valentina Stefanova
2024
Assessing Reading Literacy of Bulgarian Pupils with Finger–tracking
Alessandro Lento
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Andrea Nadalini
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Marcello Ferro
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Claudia Marzi
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Vito Pirrelli
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Tsvetana Dimitrova
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Hristina Kukova
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Valentina Stefanova
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Maria Todorova
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Svetla Koeva
Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)
The paper reports on the first steps in developing a time-stamped multimodal dataset of reading data by Bulgarian children. Data are being collected, structured and analysed by means of ReadLet, an innovative infrastructure for multimodal language data collection that uses a tablet as a reader’s front-end. The overall goal of the project is to quantitatively analyse the reading skills of a sample of early Bulgarian readers collected over a two-year period, and compare them with the reading data of early readers of Italian, collected using the same protocol. We illustrate design issues of the experimental protocol, as well as the data acquisition process and the post-processing phase of data annotation/augmentation. To evaluate the potential and usefulness of the Bulgarian dataset for reading research, we present some preliminary statistical analyses of our recently collected data. They show robust convergence trends between Bulgarian and Italian early reading development stages.
2019
On Hidden Semantic Relations between Nouns in WordNet
Tsvetana Dimitrova
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Valentina Stefanova
Proceedings of the 10th Global Wordnet Conference
The paper presents an effort on transferability of noun–verb and noun–adjective derivative and semantic relations to noun-noun relations. The approach relies on information from semantic classes and existing inter-POS derivative and (morpho)semantic relations between noun and verb, and noun and adjective synsets. We have added semantic relations between nouns in WordNet that are indirectly linked via verbs and adjectives. Observations on the combination between the relations and semantic classes of nouns they link, may facilitate further efforts in assigning semantic properties to nouns pointing to their abilities to participate in predicate-argument structures.
2018
Mapping WordNet Concepts with CPA Ontology
Svetla Koeva
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Cvetana Dimitrova
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Valentina Stefanova
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Dimitar Hristov
Proceedings of the 9th Global Wordnet Conference
The paper discusses the enrichment of WordNet data through merging of WordNet concepts and Corpus Pattern Analysis (CPA) semantic types. The 253 CPA semantic types are mapped to the respective WordNet concepts. As a result of mapping, the hyponyms of a synset to which a CPA semantic type is mapped inherit not only the respective WordNet semantic primitive but also the CPA semantic type.
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Co-authors
- Svetla Koeva 2
- Tsvetana Dimitrova 2
- Cvetana Dimitrova 1
- Dimitar Hristov 1
- Alessandro Lento 1
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