NewsLink: Empowering intuitive news search with knowledge graphs

News search tools help end users to identify relevant news stories. However, existing search approaches often carry out in a "black-box" process. There is little intuition that helps users understand how the results are related to the query. In this paper, we propose a novel news search fr...

Full description

Saved in:
Bibliographic Details
Main Authors: YANG, Yueji, LI, Yuchen, TUNG, Anthony
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/6207
https://ink.library.smu.edu.sg/context/sis_research/article/7210/viewcontent/newslink.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-7210
record_format dspace
spelling sg-smu-ink.sis_research-72102021-10-14T06:16:06Z NewsLink: Empowering intuitive news search with knowledge graphs YANG, Yueji LI, Yuchen TUNG, Anthony News search tools help end users to identify relevant news stories. However, existing search approaches often carry out in a "black-box" process. There is little intuition that helps users understand how the results are related to the query. In this paper, we propose a novel news search framework, called NEWSLINK, to empower intuitive news search by using relationship paths discovered from open Knowledge Graphs (KGs). Specifically, NEWSLINK embeds both a query and news documents to subgraphs, called subgraph embeddings, in the KG. Their embeddings' overlap induces relationship paths between the involving entities. Two major advantages are obtained by incorporating subgraph embeddings into search. First, they enrich the search context, leading to robust results. Second, the relationship paths linking entities inter and intra news documents can help users better understand and digest the results for the given query. Through both human and automatic evaluations, we verify that NEWSLINK can help users understand the result-to-query relatedness, while its search quality is robust and outperforms many established search approaches, including Apache Lucene and a KG-powered query expansion approach, as well as popular deep learning models, Sentence-BERT (SBERT) and DOC2VEC. 2021-04-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6207 info:doi/10.1109/ICDE51399.2021.00081 https://ink.library.smu.edu.sg/context/sis_research/article/7210/viewcontent/newslink.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Data Storage Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Databases and Information Systems
Data Storage Systems
spellingShingle Databases and Information Systems
Data Storage Systems
YANG, Yueji
LI, Yuchen
TUNG, Anthony
NewsLink: Empowering intuitive news search with knowledge graphs
description News search tools help end users to identify relevant news stories. However, existing search approaches often carry out in a "black-box" process. There is little intuition that helps users understand how the results are related to the query. In this paper, we propose a novel news search framework, called NEWSLINK, to empower intuitive news search by using relationship paths discovered from open Knowledge Graphs (KGs). Specifically, NEWSLINK embeds both a query and news documents to subgraphs, called subgraph embeddings, in the KG. Their embeddings' overlap induces relationship paths between the involving entities. Two major advantages are obtained by incorporating subgraph embeddings into search. First, they enrich the search context, leading to robust results. Second, the relationship paths linking entities inter and intra news documents can help users better understand and digest the results for the given query. Through both human and automatic evaluations, we verify that NEWSLINK can help users understand the result-to-query relatedness, while its search quality is robust and outperforms many established search approaches, including Apache Lucene and a KG-powered query expansion approach, as well as popular deep learning models, Sentence-BERT (SBERT) and DOC2VEC.
format text
author YANG, Yueji
LI, Yuchen
TUNG, Anthony
author_facet YANG, Yueji
LI, Yuchen
TUNG, Anthony
author_sort YANG, Yueji
title NewsLink: Empowering intuitive news search with knowledge graphs
title_short NewsLink: Empowering intuitive news search with knowledge graphs
title_full NewsLink: Empowering intuitive news search with knowledge graphs
title_fullStr NewsLink: Empowering intuitive news search with knowledge graphs
title_full_unstemmed NewsLink: Empowering intuitive news search with knowledge graphs
title_sort newslink: empowering intuitive news search with knowledge graphs
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/6207
https://ink.library.smu.edu.sg/context/sis_research/article/7210/viewcontent/newslink.pdf
_version_ 1770575891418578944