Title: Identification and Evaluation of Keyphrases: Fuzzy Set based Scoring and Turing Test Inspired Evaluation

Year of Publication: Dec - 2015
Page Numbers: 107-117
Authors: Pashutan Modaresi, Stefan Conrad
Conference Name: The Second International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC2015)
- United Arab Emirates


Automatic keyphrase extraction aims at extracting a compact representation of a single document, which can be used for numerous applications such as indexing, classification or summarization. Existing keyphrase extraction approaches typically consist of two steps. An extraction step to select the candidate phrases using some heuristics and a scoring phase for ranking the extracted candidate phrases based on their importance in the text. Existing approaches to automatic keyphrase extraction mainly define the set of phrases of a document as a crisp set and by scoring and ranking the phrases, they select the keyphrases of the document. In this work we define the set of phrases in a document to be a fuzzy set, and based on the membership values of the phrases, we select the ones with higher membership values as the keyphrases of the document. Moreover we propose a novel evaluation method inspired by the Turing test, which can be used for extractive summarization tasks.