Výsledky vyhledávání - "Bi, Jingping"

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PORCA: Root Cause Analysis with Partially Observed Data

Autor: Gong, Chang, Yao, Di, Wang, Jin, Li, Wenbin, Fang, Lanting, Xie, Yongtao, Feng, Kaiyu, Han, Peng, Bi, Jingping

Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used in many application domains. Reliable diagnostic conclusions are of gr

Externí odkaz: http://arxiv.org/abs/2407.05869

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STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis

Autor: Li, Wenbin, Yao, Di, Zhao, Ruibo, Chen, Wenjie, Xu, Zijie, Luo, Chengxue, Gong, Chang, Jing, Quanliang, Tan, Haining, Bi, Jingping

The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-temporal understanding capability of LLMs are somewhat limited and biased

Externí odkaz: http://arxiv.org/abs/2406.19065

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CausalMMM: Learning Causal Structure for Marketing Mix Modeling

Autor: Gong, Chang, Yao, Di, Zhang, Lei, Chen, Sheng, Li, Wenbin, Su, Yueyang, Bi, Jingping

In online advertising, marketing mix modeling (MMM) is employed to predict the gross merchandise volume (GMV) of brand shops and help decision-makers to adjust the budget allocation of various advertising channels. Traditional MMM methods leveraging

Externí odkaz: http://arxiv.org/abs/2406.16728

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AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models

Autor: Liu, Shuo, Yao, Di, Fang, Lanting, Li, Zhetao, Li, Wenbin, Feng, Kaiyu, Ji, XiaoWen, Bi, Jingping

Detecting anomaly edges for dynamic graphs aims to identify edges significantly deviating from the normal pattern and can be applied in various domains, such as cybersecurity, financial transactions and AIOps. With the evolving of time, the types of

Externí odkaz: http://arxiv.org/abs/2405.07626

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Causal Discovery from Temporal Data: An Overview and New Perspectives

Autor: Gong, Chang, Yao, Di, Zhang, Chuzhe, Li, Wenbin, Bi, Jingping

Temporal data, representing chronological observations of complex systems, has always been a typical data structure that can be widely generated by many domains, such as industry, medicine and finance. Analyzing this type of data is extremely valuabl

Externí odkaz: http://arxiv.org/abs/2303.10112

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CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution

Autor: Yao, Di, Gong, Chang, Zhang, Lei, Chen, Sheng, Bi, Jingping

Multi-touch attribution (MTA), aiming to estimate the contribution of each advertisement touchpoint in conversion journeys, is essential for budget allocation and automatically advertising. Existing methods first train a model to predict the conversi

Externí odkaz: http://arxiv.org/abs/2201.00689

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Decentralized Trust Management: Risk Analysis and Trust Aggregation

Autor: Fan, Xinxin, Liu, Ling, Zhang, Rui, Jing, Quanliang, Bi, Jingping

Decentralized trust management is used as a referral benchmark for assisting decision making by human or intelligence machines in open collaborative systems. During any given period of time, each participant may only interact with a few of other part

Externí odkaz: http://arxiv.org/abs/1909.11355

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