Text Categorization Improvement via User Interaction - Publikacja - MOST Wiedzy

Wyszukiwarka

Text Categorization Improvement via User Interaction

Abstrakt

In this paper, we propose an approach to improvement of text categorization using interaction with the user. The quality of categorization has been defined in terms of a distribution of objects related to the classes and projected on the self-organizing maps. For the experiments, we use the articles and categories from the subset of Simple Wikipedia. We test three different approaches for text representation. As a baseline we use Bag-of-Words with weighting based on Term Frequency-Inverse Document Frequency that has been used for evaluation of neural representations of words and documents: Word2Vec and Paragraph Vector. In the representation, we identify subsets of features that are the most useful for differentiating classes. They have been presented to the user, and his or her selection allow increase the coherence of the articles that belong to the same category and thus are close on the SOM.

Cytowania

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
Artificial Intelligence and Soft Computing strony 265 - 275
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Atroszko J., Szymański J., Gil D., Mora H.: Text Categorization Improvement via User Interaction// Artificial Intelligence and Soft Computing/ : Springer, 2018, s.265-275
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1007/978-3-319-91262-2_24
Weryfikacja:
Politechnika Gdańska

wyświetlono 15 razy

Publikacje, które mogą cię zainteresować

Meta Tagi