Digging in the Dirt: Extracting Keyphrases from Texts with KD

Giovanni Moretti; Rachele Sprugnoli; Sara Tonelli

Digging in the Dirt: Extracting Keyphrases from Texts with KD

Giovanni Moretti^*
, Rachele Sprugnoli
, Sara Tonelli

^*Corresponding author

Università Cattolica del Sacro Cuore

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we present a keyphrase extraction system called Keyphrase Digger (KD). The tool uses both statistical measures and linguistic information to detect a weighted list of n-grams representing the most important concepts of a text. KD is the reimplementation of an existing tool, which has been extended with new features, a high level of customizability, a shorter processing time and an extensive evaluation on different text genres in English and Italian (ie scientific articles and historical texts).

Original language	English
Title of host publication	Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015
Pages	198-203
Number of pages	6
Publication status	Published - 2015
Event	CLiC-it 2015 - Fondazione Bruno Kessler, Trento Duration: 3 Dec 2015 → 4 Dec 2015

Conference

Conference	CLiC-it 2015
City	Fondazione Bruno Kessler, Trento
Period	3/12/15 → 4/12/15

Keywords

keyphrase extraction, tool, information extraction

Cite this

@inproceedings{3d4cb6030a12434bb88396a98c15cd48,

title = "Digging in the Dirt: Extracting Keyphrases from Texts with KD",

abstract = "In this paper we present a keyphrase extraction system called Keyphrase Digger (KD). The tool uses both statistical measures and linguistic information to detect a weighted list of n-grams representing the most important concepts of a text. KD is the reimplementation of an existing tool, which has been extended with new features, a high level of customizability, a shorter processing time and an extensive evaluation on different text genres in English and Italian (ie scientific articles and historical texts).",

keywords = "keyphrase extraction, tool, information extraction, keyphrase extraction, tool, information extraction",

author = "Giovanni Moretti and Rachele Sprugnoli and Sara Tonelli",

year = "2015",

language = "English",

isbn = "978-88-99200-62-6",

pages = "198--203",

booktitle = "Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015",

note = "CLiC-it 2015 ; Conference date: 03-12-2015 Through 04-12-2015",

}

TY - GEN

T1 - Digging in the Dirt: Extracting Keyphrases from Texts with KD

AU - Moretti, Giovanni

AU - Sprugnoli, Rachele

AU - Tonelli, Sara

PY - 2015

Y1 - 2015

N2 - In this paper we present a keyphrase extraction system called Keyphrase Digger (KD). The tool uses both statistical measures and linguistic information to detect a weighted list of n-grams representing the most important concepts of a text. KD is the reimplementation of an existing tool, which has been extended with new features, a high level of customizability, a shorter processing time and an extensive evaluation on different text genres in English and Italian (ie scientific articles and historical texts).

AB - In this paper we present a keyphrase extraction system called Keyphrase Digger (KD). The tool uses both statistical measures and linguistic information to detect a weighted list of n-grams representing the most important concepts of a text. KD is the reimplementation of an existing tool, which has been extended with new features, a high level of customizability, a shorter processing time and an extensive evaluation on different text genres in English and Italian (ie scientific articles and historical texts).

KW - keyphrase extraction, tool, information extraction

UR - http://hdl.handle.net/10807/132952

M3 - Conference contribution

SN - 978-88-99200-62-6

SP - 198

EP - 203

BT - Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015

T2 - CLiC-it 2015

Y2 - 3 December 2015 through 4 December 2015

ER -

Digging in the Dirt: Extracting Keyphrases from Texts with KD

Abstract

Conference

Keywords

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