Probabilistic Relational Connectivity Analysis of Bigram Models
Küçük Resim Yok
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study demonstrates an application of probabilistic relational graph connectivity analysis in bigram models (2-gram) of texts. The probabilistic relation matrices are calculated by estimating bigram co-occurrence probabilities in word sequence of a given short text. Then, deeper probabilistic connectivity relations among word sequences can be considered by calculating powers of probabilistic relation matrix of bigram models. Cosine similarity measure is used to evaluate similarity of probabilistic connectivity patterns of lexemes in a given message. Illustrative analysis examples are presented to discuss results of sentence-wise and short text analyses.
Açıklama
International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEY
Anahtar Kelimeler
Semantic network, transitivity, graph connectivity, bigram co-occurrence probability, text comparison
Kaynak
2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
