Cluster Labeling by Word Embeddings and WordNet's Hypernymy

Hanieh Poostchi, Massimo Piccardi


Abstract
Cluster labeling is the assignment of representative labels to clusters obtained from the organization of a document collection. 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 synonymity 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.
Anthology ID:
U18-1008
Volume:
Proceedings of the Australasian Language Technology Association Workshop 2018
Month:
December
Year:
2018
Address:
Dunedin, New Zealand
Venue:
ALTA
SIG:
Publisher:
Note:
Pages:
66–70
Language:
URL:
https://www.aclweb.org/anthology/U18-1008
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/U18-1008.pdf