ECNU at 2017 eHealth task 2: Technologically assisted reviews in empirical medicine

Jiayi Chen; Su Chen; Yang Song; Hongyu Liu; Yueyao Wang; Qinmin Hu; Liang He; Yan Yang

ECNU at 2017 eHealth task 2: Technologically assisted reviews in empirical medicine

Jiayi Chen
, Su Chen
, Yang Song
, Hongyu Liu
, Yueyao Wang
, Qinmin Hu
, Liang He
, Yan Yang

School of Computer Science and Technology

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

The 2017 CLEF eHeath Task2 requires to rank the retrieval results given by medical database. The purpose is to reduce efforts that experts devote to finding indeed relevant documents. We utilize a customized Learning-to-Rank model to re-rank the retrieval result. Additionally, we adopt word2vec to represent queries and documents and compute the relevant score by cosine distance. We find that the combination of the two methods achieves a better performance.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	1866
State	Published - 2017
Event	18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017 - Dublin, Ireland Duration: 11 Sep 2017 → 14 Sep 2017

Keywords

Health information retrieval
Learning to rank
Word2vec

Cite this

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title = "ECNU at 2017 eHealth task 2: Technologically assisted reviews in empirical medicine",

abstract = "The 2017 CLEF eHeath Task2 requires to rank the retrieval results given by medical database. The purpose is to reduce efforts that experts devote to finding indeed relevant documents. We utilize a customized Learning-to-Rank model to re-rank the retrieval result. Additionally, we adopt word2vec to represent queries and documents and compute the relevant score by cosine distance. We find that the combination of the two methods achieves a better performance.",

keywords = "Health information retrieval, Learning to rank, Word2vec",

author = "Jiayi Chen and Su Chen and Yang Song and Hongyu Liu and Yueyao Wang and Qinmin Hu and Liang He and Yan Yang",

year = "2017",

language = "英语",

volume = "1866",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

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note = "18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017 ; Conference date: 11-09-2017 Through 14-09-2017",

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TY - JOUR

T1 - ECNU at 2017 eHealth task 2

T2 - 18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017

AU - Chen, Jiayi

AU - Chen, Su

AU - Song, Yang

AU - Liu, Hongyu

AU - Wang, Yueyao

AU - Hu, Qinmin

AU - He, Liang

AU - Yang, Yan

PY - 2017

Y1 - 2017

N2 - The 2017 CLEF eHeath Task2 requires to rank the retrieval results given by medical database. The purpose is to reduce efforts that experts devote to finding indeed relevant documents. We utilize a customized Learning-to-Rank model to re-rank the retrieval result. Additionally, we adopt word2vec to represent queries and documents and compute the relevant score by cosine distance. We find that the combination of the two methods achieves a better performance.

AB - The 2017 CLEF eHeath Task2 requires to rank the retrieval results given by medical database. The purpose is to reduce efforts that experts devote to finding indeed relevant documents. We utilize a customized Learning-to-Rank model to re-rank the retrieval result. Additionally, we adopt word2vec to represent queries and documents and compute the relevant score by cosine distance. We find that the combination of the two methods achieves a better performance.

KW - Health information retrieval

KW - Learning to rank

KW - Word2vec

UR - https://www.scopus.com/pages/publications/85034779360

M3 - 会议文章

AN - SCOPUS:85034779360

SN - 1613-0073

VL - 1866

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 11 September 2017 through 14 September 2017

ER -

ECNU at 2017 eHealth task 2: Technologically assisted reviews in empirical medicine

Abstract

Keywords

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