Literatur zur Informationserschließung

Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.

© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 28. April 2022)

Suchergebnisse

• 1
  Lee, Y.-Y. ; Ke, H. ; Yen, T.-Y. ; Huang, H.-H. ; Chen, H.-H.: Combining and learning word embedding with WordNet for semantic relatedness and similarity measurement.
  In: Journal of the Association for Information Science and Technology. 71(2020) no.6, S.657-670.
  
  Abstract: In this research, we propose 3 different approaches to measure the semantic relatedness between 2 words: (i) boost the performance of GloVe word embedding model via removing or transforming abnormal dimensions; (ii) linearly combine the information extracted from WordNet and word embeddings; and (iii) utilize word embedding and 12 linguistic information extracted from WordNet as features for Support Vector Regression. We conducted our experiments on 8 benchmark data sets, and computed Spearman correlations between the outputs of our methods and the ground truth. We report our results together with 3 state-of-the-art approaches. The experimental results show that our method can outperform state-of-the-art approaches in all the selected English benchmark data sets.
  
  Inhalt: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24289.
  
  Themenfeld: Semantisches Umfeld in Indexierung u. Retrieval
  Objekt: WordNet