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计算机科学技术名家讲座(十)——徐晓伟
科研办 发布时间:2019-06-10 14:37  点击:

报告题目:Multi-Resolution Models for Learning Multilevel Abstract Representations of Text

报告时间:20196月15 上午9:00

报告地点:计算机A521

报告人Professor Xiaowei Xu

报告人简介

Xiaowei Xu, a professor of Information Science at the University of Arkansas, Little Rock (UALR), received his Ph.D. degree in Computer Science at the University of Munich in 1998. Before his appointment in UALR, he was a senior research scientist in Siemens, Munich, Germany. His research spans data mining, machine learning, bioinformatics, database management systems and high-performance computing. Dr. Xu is a recipient of 2014 ACM SIGKDD Test of Time award for his contribution to the density-based clustering algorithm DBSCAN.

报告内容简介

Complex semantic meaning in natural language is hard to be mined using computational approach. Deep language models learning a hierarchical representation proved to be a powerful tool for natural language processing, text mining and information retrieval.   This course will cover the models for word embedding and learning representations of text for information retrieval and text mining. The topic includes an introduction of language models for word embedding. It is followed by a presentation of recent multi-resolution models that represent documents at multiple resolutions in term of abstract levels. More specifically, we first form a mixture of weighted representations across the whole hierarchy of a given word embedding model, so that all resolutions of the hierarchical representation are preserved for the downstream model. In addition, we combine all mixture representations from various models as an ensemble representation. Finally, the application for information retrieval and other text mining tasks is presented in the course.  

主办单位

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吉林大学软件学院

吉林大学计算机科学技术研究所

符号计算与知识工程教育部重点实验室

海战场攻防对抗仿真技术教育部重点实验室

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