Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …

Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

全面地总结推荐系统的研究现状, 旨在介绍网络推荐的算法思想, 帮助读者了解这个研究领域.
首先阐述了推荐系统研究的工业需求, 主要研究机构和成果发表的期刊会议; …

摘要互联网技术的迅猛发展把我们带进了信息爆炸的时代. 海量信息的同时呈现,
一方面使用户很难从中发现自己感兴趣的部分, 另一方面也使得大量少人问津的信息成为网络中 …

Abstract Language models (LMs) exhibit remarkable abilities to solve new tasks from just a
few examples or textual instructions, especially at scale. They also, paradoxically, struggle …

The process of computationally identifying and categorizing opinions expressed in a piece
of text is of great importance to support better understanding and services to online users in …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …

Neural retrievers based on dense representations combined with Approximate Nearest
Neighbors search have recently received a lot of attention, owing their success to distillation …

Background An association between the severity of coronavirus disease 2019 (COVID-19)
and the presence of certain chronic conditions has been suggested. However, unlike …