Cluster Labeling by Word Embeddings and WordNet’s Hypernymy

Publication Type:
Conference Proceeding
Citation:
2018
Issue Date:
2018-12-15
Metrics:
Full metadata record
Files in This Item:
Filename Description Size
ALTA_2018_paper_4.pdfAccepted Manuscript version254.72 kB
Adobe PDF
Cluster labeling is the assignment of representative labels to clusters of documents or words. Once assigned, the labels can play an important role in applications such as navigation, search and document classification. However, finding appropriately descriptive labels is still a challenging task. In this paper, we propose various approaches for assigning labels to word clusters by leveraging word embeddings and the synonymy and hypernymy relations in the WordNet lexical ontology. Experiments carried out using the WebAP document dataset have shown that one of the approaches stand out in the comparison and is capable of selecting labels that are reasonably aligned with those chosen by a pool of four human annotators.
Please use this identifier to cite or link to this item: