A Keyphrase Generation Technique Based upon Keyphrase Extraction and Reasoning on Loosely Structured Ontologies.
Dario De Nart, Carlo Tasso · 2013
Abstract. Associating meaningful keyphrases to documents and web pages is an activity that can greatly increase the accuracy of Information Retrieval and Personalization systems, but the growing amount of text data available is too large for an extensive manual annotation. On the other hand, automatic keyphrase generation, a complex task involving Natural Language Processing and Knowledge Engineering, can significantly support this activity. Several different strategies have been proposed over the years, but most of them require extensive training data, which are not always available, suffer high ambiguity and differences in writing style, are highly domain-specific, and often rely on a wellstructured knowledge that is very hard to acquire and encode. In order to overcome these limitations, we propose in this paper an innovative unsupervised and domain-independent approach that combines keyphrase extraction and keyphrase inference based on loosely structured, collaborative knowledge such as Wikipedia, Wordnik, and Urban Dictionary. Such choice introduces a higher level of abstraction in the generated KPs that allows us to determine if two texts deal with similar topics even if they do not share a word. 1