ChatGPT is becoming a new reality. In this paper, we show how to disting...
Recently, ChatGPT, a representative large language model (LLM), has gain...
Causal feature selection has recently received increasing attention in
m...
Automatic knowledge graph construction aims to manufacture structured hu...
The aim of sequential pattern mining (SPM) is to discover potentially us...
We propose a generalized framework for block-structured nonconvex
optimi...
Discovering frequent trends in time series is a critical task in data mi...
Pattern matching can be used to calculate the support of patterns, and i...
As a novel deep learning model, gcForest has been widely used in various...
Negative sequential pattern mining (SPM) is an important SPM research to...
Knowledge-aware methods have boosted a range of Natural Language Process...
Recent years have witnessed increasing interest in few-shot knowledge gr...
In the short text, the extreme short length, feature sparsity and high
a...
A time series is a collection of measurements in chronological order.
Di...
Traditional social group analysis mostly uses interaction models, event
...
Local causal structure learning aims to discover and distinguish direct
...
As from time to time it is impractical to ask agents to provide linear o...
Lexical simplification has attracted much attention in many languages, w...
Machine learning can provide deep insights into data, allowing machines ...
Lexical simplification (LS) aims to replace complex words in a given sen...
Feature selection is a crucial preprocessing step in data analytics and
...
Along with the emergence and popularity of social communications on the
...
Due to object detection's close relationship with video analysis and ima...
Network embedding represents nodes in a continuous vector space and pres...
Identifying user's identity is a key problem in many data mining
applica...
Online selection of dynamic features has attracted intensive interest in...
As an emerging research direction, online streaming feature selection de...
Support vector machines (SVMs) are invaluable tools for many practical
a...
It is difficult to find the optimal sparse solution of a manifold learni...