KX: A Flexible System for Keyphrase eXtraction

Proceedings of the 5th International Workshop on Semantic Evaluation, ACL 2010, pages 170–173, Uppsala, Sweden, 15-16 July 2010. c⃝2010 Association for Computational Linguistics KX: A flexible system for Keyphrase eXtraction Emanuele Pianta Fondazione Bruno Kessler Trento, Italy. pianta@fbk.eu Sara Tonelli Fondazione Bruno Kessler Trento, Italy. satonelli@fbk.eu Abstract In this paper we present KX, a system for key- phrase extraction developed at FBK-IRST, which exploits basic linguistic annotation combined with simple statistical measures to select a list of weighted keywords from a document. The system is flexible in that it of- fers to the user the possibility of setting pa- rameters such as frequency thresholds for col- location extraction and indicators for key- phrase relevance, as well as it allows for do- main adaptation exploiting a corpus of docu- ments in an unsupervised way. KX is also eas- ily adaptable to new languages in that it re- quires only a PoS-Tagger to derive lexical pat- terns. In the SemEval task 5 “Automatic Key- phrase Extraction from Scientific Articles”, KX performance achieved satisfactory results both in finding reader-assigned keywords and in the combined keywords subtask. 1 Introduction Keyphrases are expressions, either single words or phrases, describing the most important con- cepts of a document. As such, a list of key- phrases provides an approximate but useful char- acterization of the content of a text and can be used in a number of interesting ways both for human and automatic processing. For example, keyphrases provide a sort of quick summary of a document. This can be exploited not only in automatic summarization tasks, but also to en- able quick topic search over a number of docu- ments indexed according to their keywords, which is more precise and efficient than full-text search. Once the keywords of a document collec- tion are known, they can also be used to calculate semantic similarity between documents and to cluster the texts according to such similarity (Ricca et al, 2004). Also, keyword extraction can be used as an intermediate step for automatic sense extraction (Jones et al, 2002). For these reasons, the keyphrase extraction task proposed at SemEval 2010 raised much at- tention among NLP researchers, with 20 groups participating to the competition. In this frame- work, we presented the KX system, specifically tuned to identify keyphrases in scientific articles. In particular, the challenge comprised two sub- tasks: the extraction of reader-assigned and of author-assigned keyphrases in scientific articles from the ACM digital library. The former are assigned to the articles by annotators, who can choose only keyphrases that occur in the docu- ment, while author-assigned keyphrases are not necessarily included in the text. 2 KX architecture A previous version of the KX system, named KXPat (Pianta, 2009), was developed to extract keyphrases from patent documents in the PatEx- pert project (www.patexpert.org). The sys- tem employed in the SemEval task has additional parameters and has been tailored to identify key- phrases in scientific articles. With KX, the identification of keyphrases can be accomplished with or without the help …

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