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SmartPub : A Platform for Long-Tail Entity Extraction from Scientific Publications. / Mesbah, Sepideh; Bozzon, Alessandro; Lofi, Christoph; Houben, Geert-Jan.

Companion Proceedings of the The Web Conference 2018. Geneva : International World Wide Web Conferences Steering Committee, 2018. p. 191-194.

Research output: Scientific - peer-reviewConference contribution

Harvard

Mesbah, S, Bozzon, A, Lofi, C & Houben, G-J 2018, SmartPub: A Platform for Long-Tail Entity Extraction from Scientific Publications. in Companion Proceedings of the The Web Conference 2018. International World Wide Web Conferences Steering Committee, Geneva, pp. 191-194, WWW 2018, Lyon, France, 23/04/18. DOI: 1145/3184558.3186976

APA

Mesbah, S., Bozzon, A., Lofi, C., & Houben, G-J. (2018). SmartPub: A Platform for Long-Tail Entity Extraction from Scientific Publications. In Companion Proceedings of the The Web Conference 2018 (pp. 191-194). Geneva: International World Wide Web Conferences Steering Committee. DOI: 1145/3184558.3186976

Vancouver

Mesbah S, Bozzon A, Lofi C, Houben G-J. SmartPub: A Platform for Long-Tail Entity Extraction from Scientific Publications. In Companion Proceedings of the The Web Conference 2018. Geneva: International World Wide Web Conferences Steering Committee. 2018. p. 191-194. Available from, DOI: 1145/3184558.3186976

Author

Mesbah, Sepideh ; Bozzon, Alessandro ; Lofi, Christoph ; Houben, Geert-Jan. / SmartPub : A Platform for Long-Tail Entity Extraction from Scientific Publications. Companion Proceedings of the The Web Conference 2018. Geneva : International World Wide Web Conferences Steering Committee, 2018. pp. 191-194

BibTeX

@inbook{df14aed1ba1548df94cef947e3ab5cdb,
title = "SmartPub: A Platform for Long-Tail Entity Extraction from Scientific Publications",
abstract = "This demo presents SmartPub, a novel web-based platform that supports the exploration and visualization of shallow meta-data (e.g., author list, keywords) and deep meta-data--long tail named entities which are rare, and often relevant only in specific knowledge domain--from scientific publications. The platform collects documents from different sources (e.g. DBLP and Arxiv), and extracts the domain-specific named entities from the text of the publications using Named Entity Recognizers (NERs) which we can train with minimal human supervision even for rare entity types. The platform further enables the interaction with the Crowd for filtering purposes or training data generation, and provides extended visualization and exploration capabilities. SmartPub will be demonstrated using sample collection of scientific publications focusing on the computer science domain and will address the entity types Dataset (i.e. dataset presented or used in a publication), and Methods (i.e. algorithms used to create/enrich/analyse a data set)",
keywords = "Information Extraction",
author = "Sepideh Mesbah and Alessandro Bozzon and Christoph Lofi and Geert-Jan Houben",
year = "2018",
doi = "1145/3184558.3186976",
pages = "191--194",
booktitle = "Companion Proceedings of the The Web Conference 2018",
publisher = "International World Wide Web Conferences Steering Committee",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - SmartPub

T2 - A Platform for Long-Tail Entity Extraction from Scientific Publications

AU - Mesbah,Sepideh

AU - Bozzon,Alessandro

AU - Lofi,Christoph

AU - Houben,Geert-Jan

PY - 2018

Y1 - 2018

N2 - This demo presents SmartPub, a novel web-based platform that supports the exploration and visualization of shallow meta-data (e.g., author list, keywords) and deep meta-data--long tail named entities which are rare, and often relevant only in specific knowledge domain--from scientific publications. The platform collects documents from different sources (e.g. DBLP and Arxiv), and extracts the domain-specific named entities from the text of the publications using Named Entity Recognizers (NERs) which we can train with minimal human supervision even for rare entity types. The platform further enables the interaction with the Crowd for filtering purposes or training data generation, and provides extended visualization and exploration capabilities. SmartPub will be demonstrated using sample collection of scientific publications focusing on the computer science domain and will address the entity types Dataset (i.e. dataset presented or used in a publication), and Methods (i.e. algorithms used to create/enrich/analyse a data set)

AB - This demo presents SmartPub, a novel web-based platform that supports the exploration and visualization of shallow meta-data (e.g., author list, keywords) and deep meta-data--long tail named entities which are rare, and often relevant only in specific knowledge domain--from scientific publications. The platform collects documents from different sources (e.g. DBLP and Arxiv), and extracts the domain-specific named entities from the text of the publications using Named Entity Recognizers (NERs) which we can train with minimal human supervision even for rare entity types. The platform further enables the interaction with the Crowd for filtering purposes or training data generation, and provides extended visualization and exploration capabilities. SmartPub will be demonstrated using sample collection of scientific publications focusing on the computer science domain and will address the entity types Dataset (i.e. dataset presented or used in a publication), and Methods (i.e. algorithms used to create/enrich/analyse a data set)

KW - Information Extraction

U2 - 1145/3184558.3186976

DO - 1145/3184558.3186976

M3 - Conference contribution

SP - 191

EP - 194

BT - Companion Proceedings of the The Web Conference 2018

PB - International World Wide Web Conferences Steering Committee

ER -

ID: 39999403