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

^*Autore corrispondente per questo lavoro

Università Cattolica del Sacro Cuore

Risultato della ricerca: Contributo in libro › Contributo a conferenza

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).

Lingua originale	Inglese
Titolo della pubblicazione ospite	Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015
Pagine	198-203
Numero di pagine	6
Stato di pubblicazione	Pubblicato - 2015
Evento	CLiC-it 2015 - Fondazione Bruno Kessler, Trento Durata: 3 dic 2015 → 4 dic 2015

Convegno

Convegno	CLiC-it 2015
Città	Fondazione Bruno Kessler, Trento
Periodo	3/12/15 → 4/12/15

Keywords

keyphrase extraction, tool, information extraction

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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",

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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

Convegno

Keywords

Altri file e collegamenti

Fingerprint

Cita questo