research-article

An End-to-End Tool for News Processing and Semantic Search

Authors:

Satish Avadhanam,

Qiong ZhangAuthors Info & Claims

WWW '20: Companion Proceedings of the Web Conference 2020

Pages 139 - 142

https://doi.org/10.1145/3366424.3383527

Published: 20 April 2020 Publication History

Abstract

In this demonstration, we present an intelligent system for business analysis and market research that can produce actionable competitive and strategic insight. It has two sub systems, a news content processing pipeline and a semantic search engine. The pipeline collects global business news and processes them to establish context, themes, topics, entities, sentiment and relationships. The semantic search system integrates all the information produced by the pipeline and provides users the semantic search and information exploration ability. This paper introduces all the components of this system.

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Cited By

Özlü ÖOrman GDaniş FTurhan SKara KYücel T(2022)Similarity-Based Résumé Matching via Triplet Loss with BERT ModelsIntelligent Systems and Applications10.1007/978-3-031-16075-2_37(520-532)Online publication date: 1-Sep-2022
https://doi.org/10.1007/978-3-031-16075-2_37
Ullah IKhusro SAhmad I(2020)Improving social book search using structure semantics, bibliographic descriptions and social metadataMultimedia Tools and Applications10.1007/s11042-020-09811-8Online publication date: 3-Oct-2020
https://doi.org/10.1007/s11042-020-09811-8

Index Terms

An End-to-End Tool for News Processing and Semantic Search

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

WWW '20: Companion Proceedings of the Web Conference 2020

April 2020

854 pages

ISBN:9781450370240

DOI:10.1145/3366424

Editors:
Amal El Fallah Seghrouchni
Sorbonne University, France
,
Gita Sukthankar
University of Central Florida, United States
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2020

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WWW '20: The Web Conference 2020

April 20 - 24, 2020

Taipei, Taiwan

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Cited By

Özlü ÖOrman GDaniş FTurhan SKara KYücel T(2022)Similarity-Based Résumé Matching via Triplet Loss with BERT ModelsIntelligent Systems and Applications10.1007/978-3-031-16075-2_37(520-532)Online publication date: 1-Sep-2022
https://doi.org/10.1007/978-3-031-16075-2_37
Ullah IKhusro SAhmad I(2020)Improving social book search using structure semantics, bibliographic descriptions and social metadataMultimedia Tools and Applications10.1007/s11042-020-09811-8Online publication date: 3-Oct-2020
https://doi.org/10.1007/s11042-020-09811-8

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