Information Retrieval - 26th China Conference, CCIR 2020, Xi'an, China, August 14-16, 2020, Proceedings

This book constitutes the refereed proceedings of the 26th China Conference on Information Retrieval, CCIR 2020, held in Xi'an, China, in August 2020.*The 12 full papers presented were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections: search and recommendation, NLP for IR, and IR in finance.
* Due to the COVID-19 pandemic the conference was held online supplemented with local on-site events.

List of contents

Search and Recommendation.- Improving Search Snippets in Context-aware Web Search Scenarios.- Investigating Fine-grained Usefulness Perception Process in Mobile Search.- ResFusion: A Residual Learning based Fusion Framework for CTR Prediction.- NLP for IR.- A Framework for Identifying Event's Relevance Comments in Twitter.- Enriching Pre-trained Language Model with Dependency Syntactic Information for Chemical-Protein Interaction Extraction.- Leveraging Label Semantics and Correlations for Judgment Prediction.- Position-aware hybrid attention network for Aspect-level Sentiment Analysis.- IR in Finance.- An Integrated Machine Learning Framework for Stock Price Prediction.- Empirical Research on Futures Trading Strategy Based on Time Series Algorithm.- Hierarchical Attention Network in Stock Prediction.- Online Topic Detection and Tracking System and its Application on Stock Market in China.- Semi-Supervised Sentiment Analysis for Chinese Stock Texts in Scarce Labeled Data Scenario and Price Prediction.

Product details

• Assisted by: Zhicheng Dou (Editor), Guang Jia (Editor), Wei Lu (Editor), Wei Lu et al (Editor), Jiaxin Mao (Editor), Qiguan Miao (Editor), Qiguang Miao (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 31.10.2020
• EAN: 9783030567248
• ISBN: 978-3-0-3056724-8
• No. of pages: 161
• Dimensions: 160 mm x 10 mm x 237 mm
• Weight: 277 g
• Illustrations: XII, 161 p. 48 illus., 42 illus. in color.
• Series: Lecture Notes in Computer Science; Theoretical Computer Science and General Issues
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT